Metadata-Version: 2.4
Name: lynx-mcp
Version: 1.9.0
Summary: LynxMCP: 100% local MCP server for the code questions grep can't answer. Call graph and blast radius, hybrid BM25 + dense code search on ONNX Runtime, library docs and PDFs as sources. No cloud, no PyTorch.
Author: Lorenzo Cambiaghi
License:                                  Apache License
                                   Version 2.0, January 2004
                                http://www.apache.org/licenses/
        
           TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
        
           1. Definitions.
        
              "License" shall mean the terms and conditions for use, reproduction,
              and distribution as defined by Sections 1 through 9 of this document.
        
              "Licensor" shall mean the copyright owner or entity authorized by
              the copyright owner that is granting the License.
        
              "Legal Entity" shall mean the union of the acting entity and all
              other entities that control, are controlled by, or are under common
              control with that entity. For the purposes of this definition,
              "control" means (i) the power, direct or indirect, to cause the
              direction or management of such entity, whether by contract or
              otherwise, or (ii) ownership of fifty percent (50%) or more of the
              outstanding shares, or (iii) beneficial ownership of such entity.
        
              "You" (or "Your") shall mean an individual or Legal Entity
              exercising permissions granted by this License.
        
              "Source" form shall mean the preferred form for making modifications,
              including but not limited to software source code, documentation
              source, and configuration files.
        
              "Object" form shall mean any form resulting from mechanical
              transformation or translation of a Source form, including but
              not limited to compiled object code, generated documentation,
              and conversions to other media types.
        
              "Work" shall mean the work of authorship, whether in Source or
              Object form, made available under the License, as indicated by a
              copyright notice that is included in or attached to the work
              (an example is provided in the Appendix below).
        
              "Derivative Works" shall mean any work, whether in Source or Object
              form, that is based on (or derived from) the Work and for which the
              editorial revisions, annotations, elaborations, or other modifications
              represent, as a whole, an original work of authorship. For the purposes
              of this License, Derivative Works shall not include works that remain
              separable from, or merely link (or bind by name) to the interfaces of,
              the Work and Derivative Works thereof.
        
              "Contribution" shall mean any work of authorship, including
              the original version of the Work and any modifications or additions
              to that Work or Derivative Works thereof, that is intentionally
              submitted to Licensor for inclusion in the Work by the copyright owner
              or by an individual or Legal Entity authorized to submit on behalf of
              the copyright owner. For the purposes of this definition, "submitted"
              means any form of electronic, verbal, or written communication sent
              to the Licensor or its representatives, including but not limited to
              communication on electronic mailing lists, source code control systems,
              and issue tracking systems that are managed by, or on behalf of, the
              Licensor for the purpose of discussing and improving the Work, but
              excluding communication that is conspicuously marked or otherwise
              designated in writing by the copyright owner as "Not a Contribution."
        
              "Contributor" shall mean Licensor and any individual or Legal Entity
              on behalf of whom a Contribution has been received by Licensor and
              subsequently incorporated within the Work.
        
           2. Grant of Copyright License. Subject to the terms and conditions of
              this License, each Contributor hereby grants to You a perpetual,
              worldwide, non-exclusive, no-charge, royalty-free, irrevocable
              copyright license to reproduce, prepare Derivative Works of,
              publicly display, publicly perform, sublicense, and distribute the
              Work and such Derivative Works in Source or Object form.
        
           3. Grant of Patent License. Subject to the terms and conditions of
              this License, each Contributor hereby grants to You a perpetual,
              worldwide, non-exclusive, no-charge, royalty-free, irrevocable
              (except as stated in this section) patent license to make, have made,
              use, offer to sell, sell, import, and otherwise transfer the Work,
              where such license applies only to those patent claims licensable
              by such Contributor that are necessarily infringed by their
              Contribution(s) alone or by combination of their Contribution(s)
              with the Work to which such Contribution(s) was submitted. If You
              institute patent litigation against any entity (including a
              cross-claim or counterclaim in a lawsuit) alleging that the Work
              or a Contribution incorporated within the Work constitutes direct
              or contributory patent infringement, then any patent licenses
              granted to You under this License for that Work shall terminate
              as of the date such litigation is filed.
        
           4. Redistribution. You may reproduce and distribute copies of the
              Work or Derivative Works thereof in any medium, with or without
              modifications, and in Source or Object form, provided that You
              meet the following conditions:
        
              (a) You must give any other recipients of the Work or
                  Derivative Works a copy of this License; and
        
              (b) You must cause any modified files to carry prominent notices
                  stating that You changed the files; and
        
              (c) You must retain, in the Source form of any Derivative Works
                  that You distribute, all copyright, patent, trademark, and
                  attribution notices from the Source form of the Work,
                  excluding those notices that do not pertain to any part of
                  the Derivative Works; and
        
              (d) If the Work includes a "NOTICE" text file as part of its
                  distribution, then any Derivative Works that You distribute must
                  include a readable copy of the attribution notices contained
                  within such NOTICE file, excluding those notices that do not
                  pertain to any part of the Derivative Works, in at least one
                  of the following places: within a NOTICE text file distributed
                  as part of the Derivative Works; within the Source form or
                  documentation, if provided along with the Derivative Works; or,
                  within a display generated by the Derivative Works, if and
                  wherever such third-party notices normally appear. The contents
                  of the NOTICE file are for informational purposes only and
                  do not modify the License. You may add Your own attribution
                  notices within Derivative Works that You distribute, alongside
                  or as an addendum to the NOTICE text from the Work, provided
                  that such additional attribution notices cannot be construed
                  as modifying the License.
        
              You may add Your own copyright statement to Your modifications and
              may provide additional or different license terms and conditions
              for use, reproduction, or distribution of Your modifications, or
              for any such Derivative Works as a whole, provided Your use,
              reproduction, and distribution of the Work otherwise complies with
              the conditions stated in this License.
        
           5. Submission of Contributions. Unless You explicitly state otherwise,
              any Contribution intentionally submitted for inclusion in the Work
              by You to the Licensor shall be under the terms and conditions of
              this License, without any additional terms or conditions.
              Notwithstanding the above, nothing herein shall supersede or modify
              the terms of any separate license agreement you may have executed
              with Licensor regarding such Contributions.
        
           6. Trademarks. This License does not grant permission to use the trade
              names, trademarks, service marks, or product names of the Licensor,
              except as required for reasonable and customary use in describing the
              origin of the Work and reproducing the content of the NOTICE file.
        
           7. Disclaimer of Warranty. Unless required by applicable law or
              agreed to in writing, Licensor provides the Work (and each
              Contributor provides its Contributions) on an "AS IS" BASIS,
              WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
              implied, including, without limitation, any warranties or conditions
              of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
              PARTICULAR PURPOSE. You are solely responsible for determining the
              appropriateness of using or redistributing the Work and assume any
              risks associated with Your exercise of permissions under this License.
        
           8. Limitation of Liability. In no event and under no legal theory,
              whether in tort (including negligence), contract, or otherwise,
              unless required by applicable law (such as deliberate and grossly
              negligent acts) or agreed to in writing, shall any Contributor be
              liable to You for damages, including any direct, indirect, special,
              incidental, or consequential damages of any character arising as a
              result of this License or out of the use or inability to use the
              Work (including but not limited to damages for loss of goodwill,
              work stoppage, computer failure or malfunction, or any and all
              other commercial damages or losses), even if such Contributor
              has been advised of the possibility of such damages.
        
           9. Accepting Warranty or Additional Liability. While redistributing
              the Work or Derivative Works thereof, You may choose to offer,
              and charge a fee for, acceptance of support, warranty, indemnity,
              or other liability obligations and/or rights consistent with this
              License. However, in accepting such obligations, You may act only
              on Your own behalf and on Your sole responsibility, not on behalf
              of any other Contributor, and only if You agree to indemnify,
              defend, and hold each Contributor harmless for any liability
              incurred by, or claims asserted against, such Contributor by reason
              of your accepting any such warranty or additional liability.
        
           END OF TERMS AND CONDITIONS
        
           APPENDIX: How to apply the Apache License to your work.
        
              To apply the Apache License to your work, attach the following
              boilerplate notice, with the fields enclosed by brackets "[]"
              replaced with your own identifying information. (Don't include
              the brackets!)  The text should be enclosed in the appropriate
              comment syntax for the file format. We also recommend that a
              file or class name and description of purpose be included on the
              same "printed page" as the copyright notice for easier
              identification within third-party archives.
        
           Copyright 2026 Lorenzo Cambiaghi
        
           Licensed under the Apache License, Version 2.0 (the "License");
           you may not use this file except in compliance with the License.
           You may obtain a copy of the License at
        
               http://www.apache.org/licenses/LICENSE-2.0
        
           Unless required by applicable law or agreed to in writing, software
           distributed under the License is distributed on an "AS IS" BASIS,
           WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
           See the License for the specific language governing permissions and
           limitations under the License.
        
Project-URL: Homepage, https://github.com/lorenzo-cambiaghi/LynxMCP
Project-URL: Repository, https://github.com/lorenzo-cambiaghi/LynxMCP
Project-URL: Issues, https://github.com/lorenzo-cambiaghi/LynxMCP/issues
Keywords: mcp,mcp-server,model-context-protocol,rag,code-search,codebase,semantic-search,knowledge-graph,tree-sitter,bm25,local,claude,claude-code,cursor,call-graph,code-intelligence,impact-analysis,onnx
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: mcp<2
Requires-Dist: llama-index-core
Requires-Dist: llama-index-vector-stores-chroma
Requires-Dist: onnxruntime>=1.17
Requires-Dist: tokenizers>=0.15
Requires-Dist: huggingface_hub>=0.23
Requires-Dist: numpy>=1.24
Requires-Dist: chromadb
Requires-Dist: gitpython
Requires-Dist: watchdog
Requires-Dist: rank-bm25
Requires-Dist: tree-sitter>=0.25
Requires-Dist: tree-sitter-c-sharp
Requires-Dist: tree-sitter-python
Requires-Dist: tree-sitter-typescript
Requires-Dist: tree-sitter-javascript
Requires-Dist: tree-sitter-cpp
Requires-Dist: tree-sitter-c
Requires-Dist: tree-sitter-go
Requires-Dist: tree-sitter-rust
Requires-Dist: tree-sitter-java
Requires-Dist: tree-sitter-ruby
Requires-Dist: tree-sitter-php
Requires-Dist: tree-sitter-kotlin
Requires-Dist: tree-sitter-swift
Requires-Dist: tree-sitter-bash
Requires-Dist: tree-sitter-sql
Requires-Dist: tree-sitter-scala
Requires-Dist: tree-sitter-lua
Requires-Dist: tree-sitter-objc
Requires-Dist: networkx>=3.0
Requires-Dist: httpx>=0.27
Requires-Dist: beautifulsoup4>=4.12
Requires-Dist: trafilatura>=1.10
Requires-Dist: truststore>=0.10
Requires-Dist: pypdf>=4.0
Requires-Dist: fastapi>=0.110
Provides-Extra: dev
Requires-Dist: pytest>=7; extra == "dev"
Requires-Dist: reportlab>=4; extra == "dev"
Provides-Extra: pdf-fast
Requires-Dist: pymupdf>=1.24; extra == "pdf-fast"
Provides-Extra: webdoc-js
Requires-Dist: playwright>=1.40; extra == "webdoc-js"
Dynamic: license-file

# Lynx

**LynxMCP is a 100% local MCP server for the code questions grep can't answer: what calls this, what breaks if I change it, where is the code that does X, how does the library version I actually use behave. AST-aware chunking, hybrid BM25 + dense retrieval, an optional code knowledge graph, and your library docs and PDFs indexed next to your code. Works with any MCP client (Claude Code, Cursor, Windsurf, Antigravity, ...).**

[![Tests](https://github.com/lorenzo-cambiaghi/LynxMCP/actions/workflows/test.yml/badge.svg)](https://github.com/lorenzo-cambiaghi/LynxMCP/actions/workflows/test.yml)
[![License: Apache 2.0](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](LICENSE)
![Python 3.10+](https://img.shields.io/badge/python-3.10%2B-blue)
[![Glama score](https://glama.ai/mcp/servers/lorenzo-cambiaghi/LynxMCP/badges/score.svg)](https://glama.ai/mcp/servers/lorenzo-cambiaghi/LynxMCP)

[![LynxMCP MCP server](https://glama.ai/mcp/servers/lorenzo-cambiaghi/LynxMCP/badges/card.svg)](https://glama.ai/mcp/servers/lorenzo-cambiaghi/LynxMCP)

Grep is the right tool when you know the identifier, and your agent already has it. Lynx is for the questions grep cannot answer. Behaviour: "where do we clamp the camera zoom?" matches nothing literal. Structure: who calls this, what inherits from it, what breaks if it changes; polymorphic dispatch leaves no textual trace. Knowledge past the model's training cutoff: the docs of the framework version you run, indexed as a source. Nothing leaves your machine.

## What grep can't answer

Each row is measured; the numbers come from the [benchmarks](#benchmarks-reproducible) below.

| Question | Agentic grep | Lynx |
|---|---|---|
| "What inherits from `Field`?" (Django, 100 classes over 4 levels) | 101 grep rounds, one per discovered class | 4 `graph_query` calls, `file:line` on every edge |
| "What breaks if I change `ApplyDamage`?" | the textual mentions of the name | `impact`: every transitive caller with its hop distance, plus the tests to re-run |
| "Where do we validate session tokens?" on C# (Json.NET) | hit@1 33% | hit@1 47% |
| "How does this API behave in the version we ship?" | the model's memory | the docs you indexed, cited with the page they came from |

Where grep is better, this page says so. On Guava, whose class names document themselves (`BloomFilter`, `RateLimiter`), grep ranks higher: hit@1 73% against 60%. On a repository that fits in the agent's context, the built-in tools are fine. Lynx pays off on large codebases, on framework docs your model has gone stale on, and on repeated sessions where re-exploring from scratch is waste.

## Quickstart

```bash
# 1. Install the CLI (isolated, no venv ritual). About 460 MB on disk, no PyTorch.
pipx install lynx-mcp
#    or: uv tool install lynx-mcp

# 2. Create a config and point it at your project
lynx manager init
lynx source add myproject --type codebase --path /path/to/your/repo

# 3. Build the index (downloads the 130 MB embedding model on first run)
lynx build
```

`lynx manager init` also offers to open the web UI, where the same source can be added through a guided form with a folder picker. Everything below works either way.

Every tool your AI gets is also a command, with the same name and the same output: `lynx find-definition ApplyDamage`, `lynx impact ApplyDamage`, `lynx graph query --op callers --symbol ApplyDamage`. Add `--json` to any of them for scripts.

Then register Lynx in your MCP client. Claude Code is shown; the [full guide](docs/GUIDE.md) covers Cursor, Antigravity, and generic stdio clients, or let `lynx manager ui` generate the snippet for you:

```json
{
  "mcpServers": {
    "lynx": {
      "command": "lynx",
      "args": ["serve", "--config", "/absolute/path/to/config.json"]
    }
  }
}
```

The server answers the MCP handshake in about a second and opens the indexes in the background; a call that arrives earlier gets the loading state back and is retried. If you would rather skip the terminal, there are [double-click installers](https://github.com/lorenzo-cambiaghi/LynxMCP/releases) for macOS and Windows.

## The tools your AI gets

The tool set is fixed: it does not grow with the number of sources. It is also layered, because every tool definition rides in your client's context on every turn. Three profiles: `core` (5 tools, about 1,200 tokens of definitions), `standard` (10 tools, about 2,700 tokens, the default) and `full` (17 tools, about 3,800 tokens). Set `tools.profile` in config.json or pass `lynx serve --profile full`; `tools.include` adds a single tool to a profile. Tools take a `source` argument where relevant.

| Tool | Profile | What it answers |
|------|---------|-----------------|
| `search(query, source?, outline?)` | core | Primary hybrid search. Omit `source` to search every source at once (RRF-fused). `outline=true` returns signatures only, for cheap triage. |
| `deep_search(queries, source?)` | standard | Escalation: tries multiple query phrasings until one passes a quality threshold. |
| `graph_query(operation, symbol?)` | standard | `callers`, `callees`, `subclasses`, `superclasses`, `imports`, `neighbors`, `shortest_path`, `overview`, `surprising_connections`, `status`. |
| `find_definition(symbol)` | standard | Where is X defined? (AST-precise when the graph is on, BM25 fallback otherwise.) |
| `find_usages(symbol)` | core | Every use of X: calls *and* non-call references (generics, decorators, docs). |
| `find_tests_for(symbol)` | full | Are there tests for X? |
| `find_similar(snippet)` | full | Does code like this already exist? |
| `describe_symbol(symbol)` | core | One-shot context for X: definition, who calls it, what it calls, its tests, in a single call. |
| `impact(symbol)` | core | Blast radius: everything that reaches X *transitively* through the call graph (with hop distance), plus the tests to re-run. |
| `module_summary(file)` | full | A file as a unit: the symbols it defines, what it imports, and which files depend on it. *(graph)* |
| `repo_overview()` | standard | "What is this and where do I start": detected languages, frameworks, entry points, and build/test/run commands. |
| `export_graph(target, mode?)` | full | Render a shareable, offline graph view (a symbol's blast radius or a file hub) as a single self-contained file. *(graph)* |
| `search_diff(query, base?)` | standard | Search only the files changed vs a base branch. Built for code review. |
| `feedback(trying_to_do, tried, stuck)` | core | The agent files a report when the index couldn't answer. Stored 100% locally, your signal for tuning sources. |
| `list_sources` / `get_rag_status` / `update_source_index` | full | Introspection and maintenance. |

Retrieval tools carry MCP `readOnlyHint` annotations, so clients can auto-approve them. The only write is `export_graph`, which saves a graph view file. The server ships its usage playbook in the MCP handshake (`instructions` plus a `lynx://guide` resource), so your agent knows how to query well without any rules-file setup.

*(graph)* tools need the optional code knowledge graph enabled for the source. The tool set is per-capability, never per-source.

<p align="center">
  <img src="https://raw.githubusercontent.com/lorenzo-cambiaghi/LynxMCP/main/docs/img/graph_view_example.svg" alt="Blast-radius graph view: callers above the symbol, callees below, exported as a single offline file" width="820">
  <br>
  <sub><b>Shareable graph views</b>: <code>lynx graph export --symbol GetVoxel</code> writes one self-contained, offline file (no server, no CDN) with the symbol's <b>blast radius</b>, who calls it (above) and what it calls (below). Attach it to a PR or archive it for an audit.</sub>
</p>

## How it works

```mermaid
flowchart LR
    A["Your code + docs + PDFs"] --> B["Tree-sitter<br/>AST chunker"]
    B --> C["bge-small<br/>dense embeddings"]
    B --> D["code-tokenized<br/>BM25"]
    B --> G["Code knowledge graph<br/>(opt-in)"]
    C --> R{{"RRF fusion"}}
    D --> R
    Q(["Your query"]) --> R
    R --> RR["Optional<br/>reranker"]
    RR --> RES["Ranked code<br/>file : line : symbol"]
    G --> GT["Graph tools<br/>callers · subclasses · usages"]

    classDef store fill:#fff3e6,stroke:#e8742c,color:#24292f;
    classDef out fill:#e8742c,stroke:#e8742c,color:#fff;
    class C,D,G store;
    class RES,GT out;
```

- Tree-sitter parses 18+ languages (19 grammars, counting TSX) and indexes whole functions and classes, not arbitrary text windows.
- Retrieval is hybrid: dense embeddings plus code-tokenized BM25, fused with RRF, with an optional cross-encoder reranker.
- The code knowledge graph (opt-in) records who calls what, inheritance and imports, and answers "what breaks if I change this?" with the actual blast radius.
- Sources can be codebases, public docs sites (fetched once, on demand; JS-rendered SPAs via optional headless Chromium) and PDFs, searched side by side.
- A file watcher re-indexes a saved file in about 2 seconds. No manual rebuild ritual.
- Search and the graph are also served as rows over a local HTTP API, so SQL engines can join your code with tickets, PRs or logs (see [Integrations](#integrations)).
- `lynx manager ui` gives you guided setup, a query playground, diagnostics and client config snippets in the browser.

Everything runs locally: HuggingFace models are downloaded once, then Lynx switches to offline mode. No telemetry, no cloud index, no code upload. The only network access is the model download and the *explicit* `webdoc` fetch step you trigger yourself.

The models run on ONNX Runtime, so there is no PyTorch in the install: about 460 MB on disk, and a 165 MB download on Linux where the torch wheel alone used to bring 4 GB of CUDA libraries. Same model, same vectors, so an index built by an earlier version keeps working.

Open as many sessions on one index as you like: two editor windows, an editor plus the web UI, a CLI query while the server runs. They all search the same index. Only indexing is exclusive, and the process doing it hands over automatically if you close it.

Behind a firewall or on an air-gapped machine? The model can come from a mirror, from this repo's GitHub Releases (the automatic fallback), or from an archive you carry over; see [Restricted networks](docs/GUIDE.md#restricted-networks-and-air-gapped-machines) in the guide.

<p align="center">
  <a href="docs/GUIDE.md#lynxmanager-guided-setup-web-ui-diagnostics-new-in-v09">
    <img src="https://raw.githubusercontent.com/lorenzo-cambiaghi/LynxMCP/main/readmeData/LynxManagerV.gif" alt="LynxManager: guided setup, query playground, and diagnostics in the browser" width="820">
  </a>
  <br>
  <sub><b><a href="docs/GUIDE.md#lynxmanager-guided-setup-web-ui-diagnostics-new-in-v09">LynxManager</a></b>: guided setup, query playground &amp; diagnostics, all in the browser. <a href="docs/GUIDE.md#lynxmanager-guided-setup-web-ui-diagnostics-new-in-v09">Full walkthrough</a></sub>
</p>

## Benchmarks (reproducible)

<img src="https://raw.githubusercontent.com/lorenzo-cambiaghi/LynxMCP/main/benchmarks/chart.svg" alt="Lynx vs agentic grep: fewer tokens to answer on Python, C# and Java; 4 vs 101 tool calls to map a class hierarchy" width="1000">

Three codebases, three languages, behavioural questions with known ground-truth files, and a grep baseline built to be strong (IDF-weighted multi-keyword ranking with ideal stopword removal, closer to BM25 than to an agent's first `rg`). Methodology and per-task results: [Django](benchmarks/RESULTS.md), [Json.NET](benchmarks/RESULTS_csharp.md), [Guava](benchmarks/RESULTS_java.md).

| grep / Lynx | Django 5.2 (Python) | Json.NET (C#) | Guava (Java) |
|---|---|---|---|
| corpus | 883 files, 158k lines, 20 questions | 240 files, 69k lines, 15 questions | 606 files, 181k lines, 15 questions |
| hit@5 | **95%** / 85% | 67% / **73%** | **93%** / 80% |
| hit@1 | 45% / **55%** | 33% / **47%** | **73%** / 60% |
| MRR | 0.64 / **0.67** | 0.47 / **0.58** | **0.81** / 0.70 |
| median tokens to answer | 4,150 / **1,725** | 6,590 / **1,540** | 5,892 / **807** |
| tool round-trips before the code is in context | 2+ / **1** | 2+ / **1** | 2+ / **1** |

Ranking swings with how self-documenting the code is: Lynx ahead on C#, where PascalCase identifiers and sparse comments starve a lexical baseline; mixed on Python, ahead at hit@1 and behind at hit@5 in Django's docstring-rich code; behind on Guava. The token cost does not swing. It drops 58% to 86% every time, because Lynx hands back the whole function with `file:line`, symbol and score in one call, where grep returns match lines and then needs a read.

The structural gap is of a different kind. "What inherits from `Field`?" over Django's 100-class hierarchy takes grep 101 rounds, one per discovered class, each a full model inference over the growing context; `graph_query` answers it in 4 calls from resolved inheritance edges, same recall, `file:line` on every edge.

```bash
# reproduce: Python (Django)
git clone --depth 1 --branch 5.2 https://github.com/django/django.git benchmarks/_target/django
python benchmarks/run_benchmark.py && python benchmarks/structural_demo.py

# reproduce: C# (Json.NET)
git clone --depth 1 https://github.com/JamesNK/Newtonsoft.Json.git benchmarks/_target/jsonnet
python benchmarks/run_benchmark.py --tasks benchmarks/tasks_jsonnet.json \
  --target-dir benchmarks/_target/jsonnet --storage-dir benchmarks/_storage_csharp \
  --results-json benchmarks/results_csharp.json --results-md benchmarks/RESULTS_csharp.md

# reproduce: Java (Guava)
git clone --depth 1 https://github.com/google/guava.git benchmarks/_target/guava
python benchmarks/run_benchmark.py --tasks benchmarks/tasks_guava.json \
  --target-dir benchmarks/_target/guava --storage-dir benchmarks/_storage_java \
  --results-json benchmarks/results_java.json --results-md benchmarks/RESULTS_java.md
```

## What it costs, in tokens and in money

Per retrieval, the saving is the measured delta above: 2,400 to 5,100 fewer tokens to get the answer into context. Per session, the tool definitions cost 1,200 tokens (`core`), 2,700 (`standard`) or 3,800 (`full`), so a session has paid for its tool list after the first or second retrieval. `outline` triage cuts the search step by another 2.4x on broad queries ([measured](docs/OUTLINE.md)).

In money, for 25 engineers making 60 retrievals a day (31,500 a month), the yearly API bill Lynx removes, as a range across the three codebases:

| Flagship model (input $/1M) | Measured floor | With the saved round trip |
|---|---:|---:|
| Claude Fable 5 ($10) | $9,200 to $19,200 | $16,700 to $26,800 |
| GPT-5.5, Claude Opus 4.8 ($5) | $4,600 to $9,600 | $8,400 to $13,400 |

The floor counts only the smaller tool output, no assumptions. The second column adds the one grep round trip Lynx removes, whose 20k-token context is re-read from the prompt cache at a tenth of the input price; that discount is the single modelled assumption, and it is a knob. Run it for your own team, prices and codebase: `python benchmarks/savings_calculator.py --devs N`, or the interactive [savings calculator](benchmarks/savings_calculator.html) (presets in [`pricing.json`](benchmarks/pricing.json) and [`measured.json`](benchmarks/measured.json), yours to edit).

<img src="https://raw.githubusercontent.com/lorenzo-cambiaghi/LynxMCP/main/docs/img/cost_savings.svg" alt="Yearly API bill Lynx removes, by flagship model, for the three benchmarked codebases, with prompt caching" width="880">

## Read less: outline mode

Every search ranks the same way. `search(query, outline=true)` (or `?view=outline` over HTTP) returns the same ranked hits without their bodies: a one-line signature plus the first line of the docstring, so the agent scans the candidates and reads the single body it needs, by its cited `file:line`. On a public repo (`psf/requests`) it cut the search step to 2.4x fewer tokens. When to use which, the measured data and the chart: [docs/OUTLINE.md](docs/OUTLINE.md).

## Integrations

Search and the code graph are served as NDJSON over a local HTTP API (`/api/v1`), and the MCP tools compose with any other MCP server your agent has. Everything below stays on your machine; only the other side of a join (GitHub, Jira, Sentry) touches an API.

- [Coral](docs/CORAL.md): Lynx is a community source in Coral's registry, `lynx.search` plus six graph functions, so a behavioural question becomes a SQL table you join with live GitHub or Sentry data.
- [DuckDB](docs/DUCKDB.md): `read_ndjson_auto('http://127.0.0.1:8765/api/v1/search?...')` is a table, no plugin and no daemon; join code relevance with git churn, error logs or ticket exports.
- [Steampipe](integrations/steampipe/steampipe-plugin-lynx/): a plugin with `lynx_source`, `lynx_search` and `lynx_graph` tables that join per row, one search per row of another table; prebuilt macOS and Linux binaries on the [releases page](https://github.com/lorenzo-cambiaghi/LynxMCP/releases?q=steampipe).
- [GitHub Action](integrations/github-action/): on every PR, a comment with the downstream callers and the semantically related code, indexed locally on the runner.
- [MCP recipes](docs/MCP_RECIPES.md): agent patterns combining Lynx with GitHub, Sentry and Jira MCP servers (triage, PR impact, ticket to code).

## Documentation

| | |
|---|---|
| [Full guide](docs/GUIDE.md) | Configuration, all source types (codebase / webdoc / PDF), retrieval internals, tool profiles, troubleshooting |
| [Manager UI](docs/GUIDE.md#lynxmanager-guided-setup-web-ui-diagnostics-new-in-v09) | Guided setup, playground, diagnostics |
| [Outline mode](docs/OUTLINE.md) | Signatures instead of bodies: when to use it, measured data, chart |
| [Coral](docs/CORAL.md) / [DuckDB](docs/DUCKDB.md) / [Steampipe](integrations/steampipe/steampipe-plugin-lynx/) | Code search and the code graph as SQL tables |
| [MCP recipes](docs/MCP_RECIPES.md) | Combining Lynx with GitHub / Sentry / Jira MCP servers |
| [PR impact analysis (GitHub Action)](integrations/github-action/) | Downstream callers and related code, commented on every PR |
| [config.example.json](config.example.json) | Annotated example configuration |

## Status

Developed by one author; APIs may still move before 1.x stabilizes. Issues and PRs are welcome. The test suite runs with `pytest` and CI must stay green. See [ROADMAP.md](ROADMAP.md) for what's under consideration (and what is explicitly *not* planned).

## License

[Apache 2.0](LICENSE)

---

<!-- MCP Registry ownership marker. It must stay in the README published on
     PyPI so registry.modelcontextprotocol.io can verify the package.
mcp-name: io.github.lorenzo-cambiaghi/lynx
-->
