context-bridge
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@context-bridgesearch code for database connection handler"
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.
Context Bridge
Bridge the context gap between your codebase and AI coding tools.
Context Bridge is a lightweight MCP (Model Context Protocol) server that builds a persistent semantic knowledge graph of your codebase. It enables AI assistants to query complex codebases with sub-millisecond latency, eliminating the need to re-read files every session.
Why?
AI coding tools are powerful but suffer from a context gap:
They re-read the same files in every session
They lack deep understanding of your architecture
They can't learn from your coding conventions
23 minutes of developer focus are lost per context switch
Context Bridge solves this by indexing your codebase into a local knowledge graph that persists across sessions.
Related MCP server: CodeRAG
Features
Semantic Code Search — Query code with natural language
Persistent Knowledge Graph — SQLite-based, survives restarts
Sub-millisecond Queries — FTS5 + precomputed embeddings
MCP Protocol — Works with Claude Code, Cursor, and any MCP client
Auto-indexing — Watches files and updates the index automatically
Zero Cloud — Everything runs locally
Quick Start
# Clone and install locally
git clone https://github.com/hussain-alsaibai/context-bridge.git
cd context-bridge && npm install
# Initialize in your project
cd your-project
node /path/to/context-bridge/src/server.js init
# Start the MCP server
node /path/to/context-bridge/src/server.js serve
# Or use with Claude Code
claude mcp add context-bridge -- node /path/to/context-bridge/src/server.js serveNote: the unscoped npm name
context-bridgeis owned by an unrelated third-party package, sonpm install -g context-bridgeinstalls that package instead of this one. Use the clone-and-install steps above until an official npm release under a scoped name is available.
Configuration
Create .context-bridge.json in your project root:
{
"include": ["src/**/*.{js,ts,jsx,tsx}", "lib/**/*.py"],
"exclude": ["node_modules/**", "dist/**", "*.test.js"],
"dbPath": ".context-bridge/db.sqlite",
"watch": true,
"maxFileSizeKB": 500
}MCP Tools
Tool | Description |
| Search code with natural language or regex |
| Get full context of a function/class/variable |
| Show what a file depends on |
| Find all callers of a function |
| Get a high-level summary of a module |
Architecture
┌─────────────────┐ ┌──────────────┐ ┌────────────────┐
│ Claude Code │────▶│ Context │────▶│ SQLite + FTS5 │
│ Cursor │ │ Bridge MCP │ │ Knowledge Graph│
│ Other MCP │◀────│ Server │◀────│ (persistent) │
│ Clients │ │ │ │ │
└─────────────────┘ └──────────────┘ └────────────────┘
│
▼
┌──────────────┐
│ File Watcher │
│ (auto-index) │
└──────────────┘Status
v0.2.1 — the server speaks JSON-RPC, the dialect every MCP client uses.
v0.1.0shipped on 2026-06-20 and was broken: it threw on startup, matched no files, and lost the index on every re-index. It was fixed on 2026-10-25 in commit2cc4ee9.The standalone indexer (
src/indexer.js) never indexed anything — it started the MCP server instead. Fixed in v0.2.0.v0.2.0shipped a handler that read{tool, params}. No MCP client sends that shape — clients speak JSON-RPC{jsonrpc, id, method, params}— so every real request arrived withtool === undefinedand fell through to "Unknown tool: undefined". The four existing tests stayed green because they asserted the same wrong shape. Fixed in v0.2.1 (commit688f79c), which adds a contract test that drives a real handshake over stdio.CI now runs on every push and pull request: install, test, lint.
Run the test suite with npm test (7 tests).
License
MIT
This server cannot be deployed
Maintenance
Related MCP Connectors
The Cortex MCP server provides read-only access to real-time engineering context from the Cortex developer portal, allowing AI coding assistants to answer natural language questions about your organization's catalog (microservices, libraries, domains, teams, infrastructure), scorecards (engineering standards and best practices), initiatives (goals and deadlines), and Engineering Intelligence metrics. It includes tools for querying documentation, tracking personal entities, and accessing AI-assisted insights across the entire Cortex ecosystem.
Intelligent context infrastructure for AI teams: knowledge graph, sessions, tasks, documents.
One shared context your team's AI tools read & write over MCP. No re-explaining. Free.
The context platform for AI agents: code search, team decisions, and grounded project context.
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