RADIX L1 TRIE // 0.06MS CROSS-PROVIDER REPLAY RFC 7636 MCP NATIVE

Cut your LLM bill by 85%.
Kill 90% of prompt latency.

The transparent localhost proxy for Claude Code, Cursor, and autonomous AI agents. Delivers unified cross-provider caching (Claude, GPT, Ollama), instant deterministic tool-call replay from Git working trees, and team-shared memory from SQLite WAL at $0.00 token cost in <0.1ms.

Start Free with Google (1,000 Req) Inspect Architecture ↓ Open Live Dashboard ↗

omnicache-daemon ~ proxy-interceptor:8000

● LIVE WAL

# Request Intercepted from Claude Code CLI

CLOUD MISS GET package.json (mtime: 172651100)

→ Upstream Anthropic API (Roundtrip: 1,840ms | 4,210 tokens | $0.063)

WAL HIT GET package.json (Git SHA: 9f8a2c unchanged)

⚡ Served from Radix L1 Memory (0.06ms | 0 tokens | $0.00)

NET LATENCY: -99.96% SAVED: 4,210 TOKENS ($0.00)

< 0.1ms

Cache Hit Latency

85.4%

Avg Token Savings

0 Code

Drop-In SDK Changes

RFC 7636

Native MCP OAuth

FIG 01.4 // SYSTEM ARCHITECTURAL DRAFT // SPEC-MCP-2026

HOW OMNICACHE INTERCEPTS & REPLAYS

LATENCY TARGET: <0.1ms DETERMINISTIC

FRESHNESS: SHA-256 GIT WORKING TREE

MATCH METHOD: RADIX L1 + FUZZY SUBWORD

STAGE 01 ⌖ INT-01

Sidecar Intercept

Transparently intercepts OpenAI, Anthropic, and MCP tool requests on localhost port 8000.

TARGET 127.0.0.1:8000

OVERHEAD 0.02ms

STAGE 02 ⌖ L1-TRIE

L1 Radix Lookup

Deterministic O(k) prefix tree matches prompts & verifies Git SHA-256 to prevent stale cache.

LOOKUP 0.06ms

VERIFY Git SHA-256

STAGE 03 ⌖ FUZZY-PROJ

Subword Lexical Match

Projects subword tokens & hashes n-grams to detect lexical matches with zero external calls.

METHOD Fuzzy Subword

OVERHEAD <0.05ms Local

STAGE 04 ⌖ WAL-MEM

Zero-Token Replay

On cache hit, replays file contents & tool results directly from SQLite WAL for $0.00 cost.

COST $0.00 / 0 Tok

SPEED <0.1ms Replay

STAGE 05 ⌖ CMP-UP

Prune & Cloud Turn

On cache miss, compacts redundant head/tail context, routes to upstream cloud, and writes to WAL.

FALLBACK Anthropic/OpenAI

PERSIST Async SQLite

[WITHOUT OMNICACHE - DIRECT FRONTIER CLOUD]

• Average Turn Latency: 1,850ms - 3,200ms

• Cost per Re-Read Turn: $0.04 - $0.15

• Rate Limit Vulnerability: Frequent 429 Failures

[WITH OMNICACHE SIDECAR - LOCALHOST WAL]

• Cache Hit Latency: 0.06ms - 0.09ms (99.9% faster)

• Cost per Re-Read Turn: $0.00 (Zero Token Burn)

• Data Privacy & Security: 100% Air-Gapped Localhost

Live Interactive Simulator

See Fuzzy Lexical & Prefix Matching In Action

omnicache-simulator ~ fuzzy-projection-engine

● LIVE CLUSTER

Select a Prompt Scenario to Test:

Direct Upstream (OpenAI GPT-4o)

Latency: 1,420 ms

Inference Cost: $0.0245

Tokens Billed: 540 tokens

Cache Status: BYPASS / FULL COST

"Tokyo is currently experiencing mild spring weather with an average temperature of 18°C (64°F) and moderate humidity..."

⚡ OmniCache Fuzzy Lexical Hit (98.4% Match)

Latency: 0.8 ms (1,775x faster)

Inference Cost: $0.0000 (100% saved)

Tokens Billed: 0 tokens ($ avoided)

Match Method: fuzzy_lexical_subword_projection

"Tokyo is currently experiencing mild spring weather with an average temperature of 18°C (64°F) and moderate humidity..."

Architecture & Superpowers

Built For Serious AI Engineers

🔄

Cross-Provider Cache Fabric

Break out of vendor silos. While native caching is locked inside OpenAI or Anthropic, OmniCache normalizes and matches prompts across Claude, GPT-4o, Ollama, and DeepSeek with unified zero-cost replay.

🛠️

Deterministic Tool-Call Replay

Upstream AI providers never cache tool executions. When Claude Code or Cursor reads unchanged files, runs idempotent bash commands, or inspects Git state, OmniCache replays outputs from SQLite WAL in <0.1ms at $0.00 cost.

👥

Team-Shared Workspace Caching

Native provider caching is ephemeral (5-minute TTL) and strictly per-API-key. OmniCache synchronizes warm cache memory across your whole development team, multiple Cursor seats, and CI/CD pipelines.

⚡

Zero SDK Rewrite

Change just one string: point base_url to http://localhost:8000/v1. Works out-of-the-box with official openai, anthropic, LangChain, and Cursor.

🤖

Model Context Protocol (MCP)

Native RFC 7636 PKCE JSON-RPC 2.0 streaming server. Built for Claude Connectors, Claude Code CLI sidecars, and Cursor agent extensions with zero setup friction.

🛡️

Virtual Keys & Spend Caps

Assign virtual API keys to developers, apps, or subagents. Enforce hard monthly budget caps and sliding-window rate limits atomically with check-and-reserve TOCTOU protection.

10-Second Setup

Drop-In Integration

from openai import OpenAI

# 1. Point base_url to your OmniCache proxy
client = OpenAI(
    base_url="https://omnicache.rawwgrid.com/v1",
    api_key="omni_live_your_virtual_key"  # or upstream OPENAI_API_KEY
)

# 2. Make requests as normal — cross-provider caching & tool replay is automatic!
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Explain vector indexing in 3 bullet points"}]
)

print(response.choices[0].message.content)

Empirical Benchmarks

OmniCache vs Traditional Approaches

Architecture	Hit Latency	Cross-Provider	Tool-Call Replay	Team Memory	Air-Gapped Local
⚡ OmniCache Proxy	<0.1 ms	✓ Unified (Claude + GPT + Ollama)	✓ Deterministic $0.00 Replay	✓ Team-Shared SQLite WAL	✓ 100% Localhost
Native Provider Caching (Anthropic/OpenAI)	400 - 1,200 ms	✗ Siloed to 1 Provider	✗ Not Cached Upstream	✗ 5-Min Ephemeral / Key	✗ Cloud Only
Redis / Memcached DIY	15 - 25 ms	⚠️ Manual Code Logic	✗ None	⚠️ Key Sync Only	✓ Self-Hosted
Remote Gateway (Portkey / Helicone)	60 - 150 ms	✓ Multi-Provider	✗ None	✓ Cloud Stored	✗ Remote Cloud Logged

Transparent Developer Pricing

Start Free. Scale Painlessly.

Localhost speed with local UPI & card billing. Protected with hard monthly upstream spend caps and sub-millisecond replay.

Community

₹0 / forever

Perfect for testing, personal agents, and solo hobbyist workflows.

$15/mo (~₹1,250) upstream spend cap
60 requests / min rate limit
1 Workspace configuration
Sub-0.1ms L1 Radix exact cache
Deterministic tool-call replay
Instant Google Sign-In

Get Started Free

Developer Pro

₹499 / month (~$6 USD)

For active developers running Claude Code, Cursor, and daily agent loops.

$100/mo (~₹8,300) upstream spend limit
120 requests / min rate limit
Up to 5 Workspaces
Cross-provider cache (Claude + GPT + Ollama)
Deterministic tool-call replay
Instant Razorpay UPI / RuPay / Cards
VIP Support Channel

Upgrade to Pro (₹499)

Team Scale

₹1,999 / month (~$24 USD)

For fast-shipping teams sharing prompt contexts and multi-agent pipelines.

$500/mo (~₹41,500) upstream spend limit
300 requests / min rate limit
Unlimited Workspaces & seats
Team-Shared Workspace State Sync
Cross-developer deterministic tool cache
Custom Domain SSL integration
Priority 24/7 SLA

Upgrade to Team (₹1,999)

Enterprise

₹5,999 / month (~$72 USD)

Dedicated cloud clusters, VPC on-prem deployment, and enterprise compliance.

$2,000/mo (~₹1,65,000) upstream spend limit
1,000 requests / min rate limit
Dedicated cluster node / VPC
SAML SSO & Custom OAuth
Full PII & DLP Audit Logging
99.99% Uptime Guarantee
Dedicated Support Engineer

Contact Enterprise

Engineering FAQs

Frequently Asked Questions

Everything you need to know about Model Context Protocol (MCP), Model Cascading (MCB), cross-provider caching, and local privacy.

MCP How does OmniCache integrate with Model Context Protocol (MCP)?

OmniCache operates as a native RFC 7636 PKCE Model Context Protocol (MCP) streaming server on http://127.0.0.1:8000/mcp. It seamlessly bridges to Claude Desktop, Claude Code CLI, and Cursor via standard JSON-RPC 2.0. When an autonomous coding agent triggers tool executions (e.g. read_file, bash, or codebase search), OmniCache intercepts the call, verifies the Git working tree SHA-256, and replays identical executions directly from SQLite WAL memory in <0.1ms at $0.00 token cost without invoking the upstream frontier model.

CORE How does OmniCache differ from Anthropic & OpenAI native caching?

Native prompt caching from Anthropic or OpenAI has three structural limitations that OmniCache solves:

1. Provider Silos: Anthropic's cache only works for Claude; OpenAI's only works for GPT. OmniCache provides a cross-provider cache fabric where common prompt turns and tool outputs are shared across Claude, GPT-4o, DeepSeek, and Ollama.
2. Zero Tool-Call Replay: Upstream providers only cache raw text prompt prefixes—they never cache tool executions. OmniCache replays expensive file reads and shell commands deterministically.
3. Ephemeral & Per-Key: Native provider caching expires quickly (e.g. 5-minute TTL) and cannot be shared across multiple developer API keys. OmniCache shares warm cache state across your entire engineering team and CI/CD runs.

MCB What is Model Cascading (MCB) and how does fallback routing work?

Model Cascading (MCB / Model Cascading Bridge) dynamically routes LLM requests based on prompt complexity and upstream provider health:

• Complexity Delegation: Simple factual queries, syntax formatting, and repetitive prompts are automatically delegated to fast, low-cost models (e.g. gpt-4o-mini or claude-3-5-haiku), saving up to 90% compared to frontier models.
• Graceful Fallback: If an upstream cloud provider triggers an HTTP 429 Rate Limit or service outage, OmniCache transparently cascades the request to an equivalent healthy model without crashing your agent session.

FRESH How does OmniCache prevent stale cache hits when code changes?

OmniCache binds each cached tool call and prompt turn to the developer's Git working tree SHA-256 and file modification timestamps (mtime). If you edit a file, run a build, or switch Git branches, the cache key immediately invalidates. You receive fresh disk output instantly—avoiding stale hallucinations while preserving sub-millisecond replays for all unchanged context.

PRIVACY Is my source code or prompt data sent to external cloud servers?

No. OmniCache runs 100% locally on localhost (127.0.0.1:8000). All prompts, responses, tool executions, and tokens are stored in your private, local SQLite WAL database on your own machine. There is zero telemetry, zero cloud prompt logging, and zero external vector DB dependence. For team and enterprise deployments, OmniCache runs inside your own private VPC.

BILLING How does INR billing and USD spend protection work?

OmniCache offers transparent, developer-friendly billing powered by Razorpay in Indian Rupees (INR) with instant UPI, RuPay, and domestic credit/debit card checkout. Because upstream LLM providers (Anthropic, OpenAI) invoice developers in USD, OmniCache's virtual key engine enforces atomic monthly USD spend protection caps (e.g., $100/mo on Developer Pro) to ensure runaway agent loops never cause unexpected cloud billing shocks.

Cut your LLM bill by 85%. Kill 90% of prompt latency.