Which integrations are available for this server?

Powers the server's RAG capabilities by providing text embeddings, document summarization, and context synthesis using local LLMs. Utilizes SQLite with FTS5 and vector storage to manage and search document memories through both semantic similarity and full-text search.

How do I use MCP Context Hub?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MCP Context Hub search my memory for the project requirements discussed last week" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

MCP Context Hub

Local MCP server (Node.js + TypeScript) for context optimization, RAG memory, semantic cache, and sub-MCP proxy. Designed to run on a machine with GPU (RTX 3060 Ti) + Ollama, acting as a single MCP endpoint for Claude.

Architecture

Features

context_pack — Combines semantic + text search, deduplication, and LLM synthesis into a structured context bundle (summary, facts, next actions)
memory_search — Semantic similarity search over stored documents using vector embeddings
memory_upsert — Store documents with automatic chunking, embedding, and indexing
context_compress — Compress text into bullets, JSON, steps, or summary format to reduce token usage
proxy_call — Call tools on sub-MCP servers (e.g., filesystem) with optional post-processing (summarize, compress)

Requirements

Node.js >= 20
Ollama with the following models:
- llama3.1:8b-instruct-q4_K_M (primary chat)
- qwen2.5:7b-instruct-q4_K_M (fallback chat)
- nomic-embed-text:v1.5 (embeddings, 768 dims)

Quick Start

# 1. Clone and install git clone https://github.com/DiegoNogueiraDev/mcp-context-hub.git cd mcp-context-hub npm install # 2. Pull Ollama models ollama pull llama3.1:8b-instruct-q4_K_M ollama pull qwen2.5:7b-instruct-q4_K_M ollama pull nomic-embed-text:v1.5 # 3. Configure environment cp .env.example .env # Edit .env and set MCP_AUTH_TOKEN to a secure random value # 4. Start the server npm run dev

Or use the setup script:

chmod +x scripts/setup.sh ./scripts/setup.sh npm run dev

Usage

Health Check

curl http://localhost:3100/health # {"status":"healthy","timestamp":"..."}

MCP Protocol

The server uses Streamable HTTP transport at /mcp. Initialize a session first:

# Initialize session curl -X POST http://localhost:3100/mcp \ -H "Content-Type: application/json" \ -H "Accept: application/json, text/event-stream" \ -H "Authorization: Bearer <your-token>" \ -d '{ "jsonrpc": "2.0", "method": "initialize", "params": { "protocolVersion": "2025-03-26", "capabilities": {}, "clientInfo": { "name": "my-client", "version": "1.0.0" } }, "id": 1 }'

Then call tools using the mcp-session-id header from the response:

# Store a document curl -X POST http://localhost:3100/mcp \ -H "Content-Type: application/json" \ -H "Accept: application/json, text/event-stream" \ -H "mcp-session-id: <session-id>" \ -d '{ "jsonrpc": "2.0", "method": "tools/call", "params": { "name": "memory_upsert", "arguments": { "document_id": "my-doc", "content": "Your document text here...", "scope": "project", "tags": ["example"] } }, "id": 2 }' # Search memories curl -X POST http://localhost:3100/mcp \ -H "Content-Type: application/json" \ -H "Accept: application/json, text/event-stream" \ -H "mcp-session-id: <session-id>" \ -d '{ "jsonrpc": "2.0", "method": "tools/call", "params": { "name": "memory_search", "arguments": { "query": "your search query", "top_k": 5 } }, "id": 3 }'

Sub-MCP Proxy

Configure sub-MCP servers via the PROXY_SERVERS environment variable:

PROXY_SERVERS='{"filesystem":{"command":"node","args":["node_modules/@modelcontextprotocol/server-filesystem/dist/index.js","/tmp"]}}' npm run dev

Then call tools on them via proxy_call:

{ "name": "proxy_call", "arguments": { "server": "filesystem", "tool": "read_file", "arguments": { "path": "/tmp/example.txt" }, "post_process": "none" } }

Configuration

All settings via environment variables (see .env.example):

Variable	Default	Description
`MCP_AUTH_TOKEN`		Bearer token for authentication
`MCP_ALLOWED_IPS`	`127.0.0.1,::1`	Comma-separated allowed IPs
`OLLAMA_BASE_URL`	`http://localhost:11434`	Ollama API URL
`PRIMARY_MODEL`	`llama3.1:8b-instruct-q4_K_M`	Primary chat model
`FALLBACK_MODEL`	`qwen2.5:7b-instruct-q4_K_M`	Fallback chat model
`EMBEDDING_MODEL`	`nomic-embed-text:v1.5`	Embedding model
`PORT`	`3100`	Server port
`HOST`	`0.0.0.0`	Server host
`DB_PATH`	`./data/context-hub.db`	SQLite database path
`CACHE_TTL_MS`	`300000`	Cache TTL (5 minutes)
`CACHE_MAX_ENTRIES`	`100`	Max cache entries
`LOG_LEVEL`	`info`	Log level (debug, info, warn, error)
`PROXY_SERVERS`	`{}`	Sub-MCP server configs (JSON)

Commands

npm run dev # Start dev server (HTTP on :3100) npm run dev:stdio # Start in stdio mode (for local MCP testing) npm run build # Compile TypeScript npm start # Run compiled output npm test # Run tests (31 tests, 6 files) npm run typecheck # Type-check without emitting npm run health # Run health check script

Project Structure

src/ config.ts # Environment configuration index.ts # Entry point + graceful shutdown db/ connection.ts # SQLite singleton (WAL mode) migrations.ts # Table definitions (documents, chunks, FTS5, audit) cosine.ts # Cosine similarity + embedding serialization server/ mcp-server.ts # McpServer setup + tool registration transport.ts # Express + Streamable HTTP transport session.ts # Session management middleware/ auth.ts # Bearer token validation ip-allowlist.ts # IP restriction audit.ts # Tool call logging tools/ schemas.ts # Zod schemas for all tools context-pack.ts # context_pack implementation memory-search.ts # memory_search implementation memory-upsert.ts # memory_upsert implementation context-compress.ts # context_compress implementation proxy-call.ts # proxy_call implementation services/ ollama-client.ts # Ollama API (chat + embed + fallback) sqlite-vector-store.ts # Vector store (SQLite + brute-force cosine) text-search.ts # FTS5 full-text search chunker.ts # Recursive text splitter dedup.ts # Content hashing + Jaccard dedup semantic-cache.ts # LRU + TTL in-memory cache proxy-manager.ts # Sub-MCP stdio connections utils/ logger.ts # Pino structured logging metrics.ts # In-memory call metrics retry.ts # Exponential backoff retry tokens.ts # Token estimation types/ index.ts # Type re-exports ollama.ts # Ollama API types vector-store.ts # VectorStore interface tests/ unit/ # cosine, chunker, dedup, cache integration/ # sqlite vector store e2e/ # Express server

Tech Stack

Runtime: Node.js 20, TypeScript
MCP SDK: @modelcontextprotocol/sdk v1.26
HTTP: Express v5 + Streamable HTTP transport
Database: SQLite (better-sqlite3) with WAL mode, FTS5
Embeddings: Ollama nomic-embed-text:v1.5 (768 dimensions)
Chat: Ollama with automatic model fallback
Validation: Zod v4
Logging: Pino
Testing: Vitest

License

MIT

MCP Context Hub

MCP Context Hub

Architecture

Features

Requirements

Quick Start

Usage

Health Check

MCP Protocol

Sub-MCP Proxy

Configuration

Commands

Project Structure

Tech Stack

License

Resources

Latest Blog Posts

MCP directory API