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@Context-Engine-AI/Context-Engine

MCP connector for code search, memory, and symbol tools

Context Engine connects an AI coding assistant to semantic search, symbol graphs, memory, and cross-repo lookup through MCP. The repo combines the bridge, server code, assistant rules, and docs so the agent can search, trace, and recall context from a codebase instead of relying on chat history alone.

400 stars54 forksPythonUpdated 2mo ago
Who it's for

Builders who want their assistant to search code, trace symbols, and remember context across sessions.

What it delivers

You can make your agent work with a live codebase context instead of re-explaining the project every session.

What it does

Semantic search routing

Uses `search` as the default tool and routes queries to semantic search, Q&A, symbol graph, tests, or config lookups.

Symbol graph navigation

Finds definitions, callers, callees, importers, subclasses, and other code relationships with `symbol_graph`.

Batch queries

Runs `batch_search`, `batch_symbol_graph`, and `batch_graph_query` to cut token use on repeated lookups.

Persistent memory

Stores and retrieves context with `memory_store` and `memory_find` across sessions.

Cross-repo tracing

Searches across repositories and traces boundaries for multi-repo codebases.

MCP bridge and server

Provides `ctxce connect`, `ctxce mcp-serve`, and `ctxce mcp-http-serve` for terminal MCP clients and HTTP clients.

How to get it

  1. 1Recommended: Install natively from the public GitHub repo
    # Add the marketplace (one-time)
    /plugin marketplace add Context-Engine-AI/Context-Engine
    
    # Install the skill
    /plugin install context-engine
  2. 2Alternatively, copy the rules file manually
    cp -r skills/context-engine/ your-project/.claude/
  3. 3Context Engine rules are included in .cursorrules at the root of your workspace. Cursor…
    # Copy to your project root
    cp .cursorrules your-project/.cursorrules
  4. 4Or install manually
    cp -r .codex/skills/context-engine/ ~/.codex/skills/context-engine/
  5. 5Run
    cp -r .codex/skills/ your-project/.codex/skills/
  6. 6Run
    cp -r .augment/ your-project/.augment/

README

Context Engine

Context Engine

Semantic code search, memory, and symbol intelligence for AI coding assistants.

Get your free account at dev.context-engine.ai

Website · Get Started · License


Install Skills

Context Engine ships AI agent skills that teach your coding assistant how to use 30+ MCP tools for semantic search, symbol graph navigation, memory, and more.

Claude Code / Claude Desktop

Recommended: Install natively from the public GitHub repo:

# Add the marketplace (one-time)
/plugin marketplace add Context-Engine-AI/Context-Engine

# Install the skill
/plugin install context-engine

This pulls the skill directly from GitHub and auto-loads MCP tool guidance into your session.

Alternatively, copy the rules file manually:

cp -r skills/context-engine/ your-project/.claude/

Cursor

Context Engine rules are included in .cursorrules at the root of your workspace. Cursor picks this up automatically when the file is present.

# Copy to your project root
cp .cursorrules your-project/.cursorrules

Codex (OpenAI)

Recommended: Install natively using the built-in skill installer — just ask Codex:

"Install the context-engine skill from https://github.com/Context-Engine-AI/Context-Engine"

Codex will pull .codex/skills/context-engine/ (including SKILL.md and reference docs) into ~/.codex/skills/ automatically.

Or install manually:

cp -r .codex/skills/context-engine/ ~/.codex/skills/context-engine/

Windsurf

cp -r .codex/skills/ your-project/.codex/skills/

Augment Code

cp -r .augment/ your-project/.augment/

Gemini

cp GEMINI.md your-project/GEMINI.md

Any Other Assistant

The core skill file works with any AI assistant that supports custom instructions:

cp skills/context-engine/SKILL.md your-project/

Then tell your assistant: "Read SKILL.md for instructions on using Context Engine MCP tools."


CLI Setup (No VS Code)

If you use Claude Code, Codex, or another terminal-based MCP client, install the MCP bridge to connect your codebase to Context Engine without VS Code:

npm install -g @context-engine-bridge/context-engine-mcp-bridge

Quick start

# Authenticate, index your codebase, and start watching for changes
ctxce connect <your-api-key> --workspace /path/to/repo

# Run as a background daemon (recommended)
ctxce connect <your-api-key> --workspace /path/to/repo --daemon

Daemon management

ctxce status          # Check if the daemon is running
ctxce stop            # Stop the background daemon

Connect flags

FlagAliasDescription
--workspace <path>-wWorkspace root (default: cwd)
--daemon-d, --bgRun as background daemon
--interval <sec>File watch interval in seconds (default: 30)
--no-watch--onceIndex once, don't watch for changes
--skip-index--auth-onlyAuthenticate only, skip initial index

Wire up the MCP server

Once connected, point your MCP client at the bridge:

# stdio mode (for Claude Code, Codex, etc.)
ctxce mcp-serve --workspace /path/to/repo

# HTTP mode (for clients that speak HTTP)
ctxce mcp-http-serve --workspace /path/to/repo --port 30810

The daemon and MCP server share auth via ~/.ctxce/auth.json. Logs are at ~/.context-engine/daemon.log.

For full bridge documentation, see Context-Engine-MCP-Bridge.


What Do the Skills Do?

The skills teach your AI assistant to:

  • Use search as the default tool — auto-routes queries to the best backend (semantic search, Q&A, symbol graph, tests, config)
  • Navigate code with symbol_graph — find callers, callees, definitions, importers, subclasses
  • Run batch queriesbatch_search, batch_symbol_graph, batch_graph_query for 75%+ token savings
  • Store and recall knowledgememory_store and memory_find for persistent context across sessions
  • Trace cross-repo flowscross_repo_search with boundary tracing for multi-repo codebases
  • Find structural patternspattern_search for retry loops, error handling, singletons across languages
  • Search git historysearch_commits_for and change_history_for_path

See skills/context-engine/SKILL.md for the complete tool reference.


Getting Started

  1. Sign up at context-engine.ai
  2. Connect your codebase — choose one:
    • VS Code — install the Context Engine Uploader extension
    • CLInpm i -g @context-engine-bridge/context-engine-mcp-bridge && ctxce connect <api-key> --daemon
  3. Install the skill for your AI assistant (see Install Skills above)
  4. Start searching — your assistant now has access to all 30+ MCP tools

License

MIT License

© 2025 Context Engine Inc. and John Donalson.

Files in the repo

Repository payload68 top-level entries
  • .augment
  • .claude-plugin
  • .codebase
  • .codex
  • .github
  • .skills
  • .vscode
  • bench
  • config
  • ctx-mcp-bridge
  • deploy
  • dev-workspace
  • docs
  • e2e
  • mcp-proxy
  • models
  • scripts
  • skills
  • src
  • static
  • templates
  • tests
  • .cursorrules
  • .dockerignore
  • .DS_Store
  • .env
  • .env.example
  • .gitignore
  • .indexignore
  • .npmrc
  • .prettierignore
  • .prettierrc
  • .qdrantignore
  • AUTHORS
  • build-images.sh
  • CODEOWNERS
  • ctx_config.example.json
  • ctx-hook-simple.sh
  • docker-compose-bindmount-checkout.yml
  • docker-compose.openlit.yml
  • docker-compose.yml
  • Dockerfile
  • Dockerfile.indexer
  • Dockerfile.llamacpp
  • Dockerfile.mcp
  • Dockerfile.mcp-indexer
  • Dockerfile.upload-service
  • enhance1.png
  • eslint.config.js
  • GEMINI.md
  • LICENSE
  • llm.png
  • Makefile
  • NOTICE
  • package-lock.json
  • package.json
  • playwright.config.ts
  • pytest.ini
  • README.md
  • requirements.txt
  • svelte.config.js
  • test_gpu_switch.py
  • THIRD_PARTY_LICENSES
  • traces.png
  • tsconfig.json
  • useage.png
  • vectors.png
  • vite.config.ts

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