Graphify.md · community-built · atlas MCP

AI developer platforms
as traversable knowledge graphs

Eleven AI developer and agent platforms as typed, source-pinned graphs. Search concepts, compare vocabulary across vendors, inspect MCP touchpoints, traverse declared relationships, and verify source hashes from one local MCP server.

Not a general-purpose semantic search layer - if it's not a declared edge, the graph doesn't return it.
$pip install ckg-ai-platforms

"The graph doesn't guess - it traverses. Every answer traces to a declared edge."

PyPI v0.3.0 11 domains · 475 nodes · 550 typed edges local stdio MCP KRB v0.6.2 MIT Graphify.md

Eleven platform graphs

475 nodes · 550 typed CSV edges · hover to explore sample vocabulary · colored by platform family

LangChain LangGraph OpenAI Anthropic Hugging Face Bedrock Vertex / Gemini / Microsoft / Palantir

What's in the graph

LangChain
48 nodes · 50 edges

Chains · Agents · LCEL · RunnableSequence · Memory · Retrievers · LangSmith · Output Parsers

LangGraph
42 nodes · 51 edges

Graph State · StateGraph · Nodes · Edges · Cycles · Persistence · Checkpointing · Human-in-the-Loop

OpenAI API
43 nodes · 45 edges

Chat Completions · Assistants · Embeddings · DALL-E · Whisper · Function Calling · Tool Use · Batch API

Anthropic SDK
44 nodes · 43 edges

Messages API · Tool Use · Prompt Caching · Computer Use · Extended Thinking · Streaming · Batch Processing

Hugging Face
46 nodes · 49 edges

Hub · Transformers · Spaces · Datasets · Inference API · PEFT · Accelerate · Safetensors

AWS Bedrock
46 nodes · 48 edges

Converse API · Guardrails · Knowledge Bases · Agents · Model Catalog · Prompt Management · Titan Embeddings

Vertex AI
45 nodes · 48 edges

Model Garden · Gemini API · Evaluation · Fine-tuning · Pipelines · Feature Store · Vertex AI Search

AWS AgentCore
36 nodes · 46 edges

Runtime · Gateway · Memory · Identity · Observability · Strands · MCP · RAG touchpoints

Gemini Agent Platform
40 nodes · 46 edges

Vertex AI · Agent Engine · ADK · MCPToolset · A2A · Memory Bank · Evaluation · Deployment

Microsoft AI Agents
40 nodes · 50 edges

Azure AI Foundry · Semantic Kernel · MCP plugins · Agent Service · Tools · Memory · Governance

Palantir Foundry
45 nodes · 74 edges

Ontology · Object Types · Link Types · Action Types · AIP · Datasets · Provenance · Governance

Traversal examples

list_atlas()
11 domains, 475 nodes, 550 typed CSV edges

find_mcp_touchpoints()
Returns MCP concepts in AWS AgentCore, Google ADK, Microsoft Semantic Kernel,
Anthropic SDK, and related platform graphs.

get_concept_context("Palantir Ontology", "palantir-foundry")
Returns direct outgoing and incoming typed relationships plus source hash.

compare_platforms("memory")
Shows which packaged platforms declare memory-related concepts.

Install

# pip
pip install ckg-ai-platforms

# Claude Desktop
{ "mcpServers": {
  "ai-platforms": {
    "command": "uvx",
    "args": ["ckg-ai-platforms"]
  }
}}

# Python library
from ckg_ai_platforms import compare_platforms, get_concept_context
matches = compare_platforms("MCP")
context = get_concept_context("AgentCore Gateway", "aws-bedrock-agentcore")

Tools

ToolDescription
list_atlas()All packaged platform graphs with counts and source coverage
compare_platforms(query)Search one term across all vendor/platform graphs
find_mcp_touchpoints()Locate MCP-related concepts and direct relationships
get_concept_context(concept, domain)Source-pinned direct typed relationships
query_ckg(concept, domain, depth)Typed subgraph around any concept, 1-5 hops
get_prerequisites(concept, domain)Compatibility tool for upstream relationship chains
search_concepts(query, domain)Fuzzy search within any domain
ask_platform(question, domain)Natural language query with domain auto-detection

Benchmark (KRB v0.6.2 locked)

0.471
CKG Macro F1
separate public benchmark
0.123
RAG baseline
2,982 tokens · $76.23/1k
3.8x
Macro F1 vs RAG
v0.6.2 structural harness

Try it now

11 platform graphs. One install. No API key.

Give an agent a small map before it reads pages of vendor prose. The server helps it find platform concepts, compare vocabulary, inspect MCP touchpoints, traverse declared relationships, and verify sources.

Pattern: public docs to source-pinned graph to MCP tools.