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-bridge search 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.
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.
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
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
# Install globally
npm install -g context-bridge
# Initialize in your project
cd your-project
context-bridge init
# Start the MCP server
context-bridge serve
# Or use with Claude Code
claude mcp add context-bridge -- node context-bridge serveCreate .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
}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 |
┌─────────────────┐ ┌──────────────┐ ┌────────────────┐
│ Claude Code │────▶│ Context │────▶│ SQLite + FTS5 │
│ Cursor │ │ Bridge MCP │ │ Knowledge Graph│
│ Other MCP │◀────│ Server │◀────│ (persistent) │
│ Clients │ │ │ │ │
└─────────────────┘ └──────────────┘ └────────────────┘
│
▼
┌──────────────┐
│ File Watcher │
│ (auto-index) │
└──────────────┘MIT
This server cannot be deployed
Codebase graphs, caller impact analysis, and recorded project context for AI coding agents.
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.
