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Built with ❤️ by Krishna Goyal

    Codealive Mcp

    The most accurate and comprehensive Context Engine as a service, optimized for large codebases, powered by advanced GraphRAG and accessible via MCP. It enriches the context for AI agents like Codex, Claude Code, Cursor, etc., making them 35% more efficient and up to 84% faster.

    65 stars
    Python
    Updated Oct 19, 2025
    claude-code
    cursor
    graphrag
    large-codebase
    mcp
    rag

    Table of Contents

    • What is CodeAlive?
    • 🛠 Available Tools
    • 🎯 Usage Examples
    • 📚 Agent Skill
    • Table of Contents
    • 🚀 Quick Start (Remote)
    • Step 1: Get Your API Key
    • Step 2: Open Your Client Guide
    • 🚀 Quick Start (Agentic Installation)
    • 🤖 AI Client Integrations
    • 🔧 Advanced: Local Development
    • Prerequisites
    • Installation
    • Local Server Configuration
    • Running HTTP Server Locally
    • Testing Your Local Installation
    • 🌐 Community Plugins
    • 🚢 HTTP Deployment (Self-Hosted & Cloud)
    • Deployment Options
    • Docker Compose (Recommended)
    • OAuth 2.1 deployment profile
    • Connecting MCP Clients to Your Deployed Instance
    • 🪟 Windows & WSL
    • 🐞 Troubleshooting
    • Quick Diagnostics
    • Common Issues
    • Windows / WSL Issues
    • Getting Help
    • 📦 Publishing to MCP Registry
    • Privacy Policy
    • 📄 License

    Table of Contents

    • What is CodeAlive?
    • 🛠 Available Tools
    • 🎯 Usage Examples
    • 📚 Agent Skill
    • Table of Contents
    • 🚀 Quick Start (Remote)
    • Step 1: Get Your API Key
    • Step 2: Open Your Client Guide
    • 🚀 Quick Start (Agentic Installation)
    • 🤖 AI Client Integrations
    • 🔧 Advanced: Local Development
    • Prerequisites
    • Installation
    • Local Server Configuration
    • Running HTTP Server Locally
    • Testing Your Local Installation
    • 🌐 Community Plugins
    • 🚢 HTTP Deployment (Self-Hosted & Cloud)
    • Deployment Options
    • Docker Compose (Recommended)
    • OAuth 2.1 deployment profile
    • Connecting MCP Clients to Your Deployed Instance
    • 🪟 Windows & WSL
    • 🐞 Troubleshooting
    • Quick Diagnostics
    • Common Issues
    • Windows / WSL Issues
    • Getting Help
    • 📦 Publishing to MCP Registry
    • Privacy Policy
    • 📄 License

    Documentation

    CodeAlive MCP: Deepest Context Engine for your projects (especially for large codebases)

    CodeAlive Logo

    Connect your AI assistant to CodeAlive's powerful code understanding platform in seconds!

    This MCP (Model Context Protocol) server enables AI clients like Claude Code, Cursor, Claude Desktop, Continue, VS Code (GitHub Copilot), Cline, Codex, OpenCode, SourceCraft Code Assistant, SourceCraft CLI, Zed, KodaCode, GigaCode, Qwen Code, Gemini CLI, Roo Code, Goose, Kilo Code, Windsurf, Kiro, Qoder, n8n, and Amazon Q Developer to access CodeAlive's advanced semantic code search and codebase interaction features.

    What is CodeAlive?

    CodeAlive is a Context Engine for large codebases, powered by graph-based retrieval and exposed through MCP. It gives AI agents like Cursor, Claude Code, Codex, and other MCP-compatible tools precise repository context instead of forcing them to read files blindly. In our RepoQA benchmark, CodeAlive + Qwen3.6 deep reached frontier-agent quality at ~25x lower model cost, and semantic search reduced captured tokens by 45%.

    It's like Context7, but for your (large) codebases.

    It allows AI-Coding Agents to:

    • Find relevant code faster with semantic search
    • Understand the bigger picture beyond isolated files
    • Provide better answers with full project context
    • Reduce costs and time by removing guesswork

    🛠 Available Tools

    Once connected, you'll have access to these powerful tools:

    1. **get_data_sources** - List your indexed repositories and workspaces

    2. **semantic_search** - Canonical semantic search across indexed artifacts

    3. **grep_search** - Exact literal or regex text search inside file content, plus literal file-name/path matching (returns files like Form.xml even when their content never mentions the name), with line-level previews for content matches

    4. **get_repository_ontology** - Get repository-level orientation for one selected repository

    5. **get_file_tree** - Inspect a bounded file tree for one repository

    6. **read_file** - Read a repository-relative file path, optionally with a line range

    7. **fetch_artifacts** - Load the full source for relevant search hits (missing or inaccessible identifiers are reported back, not silently dropped)

    8. **get_artifact_relationships** - Expand call graph, inheritance, and reference relationships for one artifact

    9. **get_artifact_query_schema** - Inspect supported ArtifactQuery entities, fields, and examples

    10. **query_artifact_metadata** - Run read-only metadata analytics across selected repositories

    11. **chat** - Stateless, slower synthesized codebase Q&A; call only when explicitly requested

    🎯 Usage Examples

    After setup, try these commands with your AI assistant:

    • *"Show me all available repositories"* → Uses get_data_sources
    • *"Find authentication code in the user service"* → Uses semantic_search
    • *"Find the exact regex that matches JWT tokens"* → Uses grep_search
    • *"Explain how the payment flow works in this codebase"* → Usually starts with semantic_search/grep_search, then optionally uses chat

    semantic_search and grep_search should be the default tools for most agents. chat is a slower stateless synthesis fallback that can take substantially longer than retrieval, and is usually unnecessary when an agent can run a multi-step workflow with ontology, search, fetch/read, relationships, ArtifactQuery, and local file reads. If your agent supports subagents, the highest-confidence path is to delegate a focused subagent that orchestrates semantic_search and grep_search first.

    📚 Agent Skill

    For an even better experience, install the CodeAlive Agent Skill alongside the MCP server. The MCP server gives your agent access to CodeAlive's tools; the skill teaches it the best workflows and query patterns to use them effectively.

    For most agents (Cursor, Copilot, Gemini CLI, Codex, and 30+ others) — install the skill:

    bash
    npx skills add CodeAlive-AI/codealive-skills@codealive-context-engine

    For Claude Code — install the plugin (recommended), which includes the skill plus Claude-specific enhancements:

    code
    /plugin marketplace add CodeAlive-AI/codealive-skills
    /plugin install codealive@codealive-marketplace

    Table of Contents

    • Agent Skill
    • Quick Start (Remote)
    • AI Client Integrations
    • Advanced: Local Development
    • Community Plugins
    • HTTP Deployment (Self-Hosted & Cloud)
    • Windows & WSL
    • Available Tools
    • Usage Examples
    • Troubleshooting
    • Publishing to MCP Registry
    • License

    🚀 Quick Start (Remote)

    The fastest way to get started - no installation required! Our remote MCP server at https://mcp.codealive.ai/api provides instant access to CodeAlive's capabilities.

    Step 1: Get Your API Key

    1. Sign up at https://app.codealive.ai/

    2. Navigate to MCP & API

    3. Click "+ Create API Key"

    4. Copy your API key immediately - you won't see it again!

    Step 2: Open Your Client Guide

    Choose your client in the MCP integration guides and follow the current setup instructions there.

    🚀 Quick Start (Agentic Installation)

    You may ask your AI agent to install the CodeAlive MCP server for you.

    1. Copy-paste the following prompt into your AI agent. Do not include your API key in the prompt:

    code
    Add the CodeAlive MCP server by following the guide for my client at https://docs.codealive.ai/integrations/mcp
    
    Prefer the Remote HTTP option when available. Do not ask me to paste an API key into chat. When the key is needed, ask me to create a CodeAlive API key and copy it to my clipboard. After I confirm, insert it directly from the clipboard into the required secure configuration without displaying, echoing, logging, or exposing it in command arguments, command output, or model context. If you cannot safely use the clipboard without exposing the value, tell me exactly where to paste it myself.

    Then allow execution.

    2. Restart your AI agent.

    🤖 AI Client Integrations

    Client-specific configuration is maintained in the CodeAlive documentation so file paths, transports, and authentication guidance stay current.

    Start here: MCP integration guides

    ClientSetup guide
    Claude CodeClaude Code
    Claude DesktopClaude Desktop
    CursorCursor
    Visual Studio CodeVS Code
    WindsurfWindsurf
    ClineCline
    ContinueContinue
    CodexCodex
    Gemini CLIGemini CLI
    Amazon Q DeveloperAmazon Q
    OpenCodeOpenCode
    SourceCraft Code Assistant and SourceCraft CLISourceCraft
    ZedZed
    ChatGPTChatGPT
    OpenClawOpenClaw
    KodaCode, GigaCode, Roo Code, Goose, Kilo Code, Qwen Code, Kiro, Qoder, JetBrains AI Assistant, n8n, and moreOther agents

    For an unlisted client, use these generic connection details and adapt them to the client's MCP configuration format:

    • Endpoint: https://mcp.codealive.ai/api
    • Transport: Streamable HTTP
    • Authentication header: Authorization: Bearer YOUR_API_KEY_HERE

    For a private deployment, replace the endpoint with your server's /api URL. See Self-Hosting for deployment guidance.

    Connecting the server is half the setup. Coding agents may continue using their built-in search unless project instructions tell them to prefer CodeAlive. Ready-made rules for AGENTS.md, CLAUDE.md, and client-specific instruction files are in Instructing Coding Agents.

    ---

    🔧 Advanced: Local Development

    For developers who want to customize or contribute to the MCP server.

    Prerequisites

    • Python 3.11+
    • uv (recommended) or pip

    Installation

    bash
    # Clone the repository
    git clone https://github.com/CodeAlive-AI/codealive-mcp.git
    cd codealive-mcp
    
    # Setup with uv (recommended)
    uv venv
    source .venv/bin/activate  # Windows: .venv\Scripts\activate
    uv pip install -e .
    
    # Or setup with pip
    python -m venv .venv
    source .venv/bin/activate  # Windows: .venv\Scripts\activate  
    pip install -e .

    Local Server Configuration

    After installing the server locally, point your MCP client at .venv/bin/python with src/codealive_mcp_server.py as the first argument and provide CODEALIVE_API_KEY in the process environment. Client-specific configuration belongs in the MCP integration guides.

    Running HTTP Server Locally

    bash
    # Start local HTTP server
    export CODEALIVE_API_KEY="your_api_key_here"
    python src/codealive_mcp_server.py --transport http --host localhost --port 8000
    
    # Test health endpoint
    curl http://localhost:8000/health

    HTTP transport validates Host and browser Origin headers. Loopback hosts

    (localhost, 127.0.0.1, ::1) work without extra configuration. For a

    shared hostname, configure an exact allowlist:

    bash
    export CODEALIVE_MCP_ALLOWED_HOSTS="mcp.codealive.yourcompany.com"
    # Only for browser callers; ordinary MCP clients do not send Origin.
    export CODEALIVE_MCP_ALLOWED_ORIGINS="https://mcp.codealive.yourcompany.com"
    python src/codealive_mcp_server.py --transport http --host 0.0.0.0 --port 8000

    The equivalent repeatable CLI options are --allowed-host and

    --allowed-origin. Do not use * for an Internet-facing server.

    Testing Your Local Installation

    After making changes, quickly verify everything works:

    bash
    # Match pyproject.toml exactly; older uv versions reject the locked setup.
    uv --version  # expected: uv 0.11.28
    uv sync --locked --extra test
    
    # Install the repository pre-push dependency audit once per clone
    ./scripts/setup-hooks.sh
    
    # Quick smoke test (recommended)
    make smoke-test
    
    # Or run directly
    python smoke_test.py
    
    # With your API key for full testing
    CODEALIVE_API_KEY=your_key python smoke_test.py
    
    # Run unit tests
    make unit-test
    
    # Run all tests
    make test
    
    # Equivalent direct locked test run
    uv run pytest src/tests/ -q

    The smoke test verifies:

    • Server starts and connects correctly
    • All tools are registered
    • Each tool responds appropriately
    • Parameter validation works
    • Runs in ~5 seconds

    ---

    🌐 Community Plugins

    • Gemini CLI — CodeAlive Extension
    • Gemini CLI setup guide

    ---

    🚢 HTTP Deployment (Self-Hosted & Cloud)

    Deploy the MCP server as an HTTP service for team-wide access or integration with self-hosted CodeAlive instances.

    Deployment Options

    The CodeAlive MCP server can be deployed as an HTTP service using Docker. This allows multiple AI clients to connect to a single shared instance, and enables integration with self-hosted CodeAlive deployments.

    Docker Compose (Recommended)

    Create a docker-compose.yml file based on our example:

    bash
    # Download the example
    curl -O https://raw.githubusercontent.com/CodeAlive-AI/codealive-mcp/main/docker-compose.example.yml
    mv docker-compose.example.yml docker-compose.yml
    
    # Edit configuration (see below)
    nano docker-compose.yml
    
    # Start the service
    docker compose up -d
    
    # Check health
    curl http://localhost:8000/health

    Configuration Options:

    1. For CodeAlive Cloud (default):

    • Remove CODEALIVE_BASE_URL environment variable (uses default https://app.codealive.ai)
    • For remote clients with OAuth support, configure only https://mcp.codealive.ai/api and

    complete the browser sign-in when prompted

    • Existing API-key clients remain supported via Authorization: Bearer YOUR_KEY

    2. For Self-Hosted CodeAlive:

    • Set CODEALIVE_BASE_URL to your CodeAlive instance URL (e.g., https://codealive.yourcompany.com)
    • Set CODEALIVE_MCP_ALLOWED_HOSTS to the exact hostname clients use for this MCP server
    • Clients must provide their API key via Authorization: Bearer YOUR_KEY header

    See docker-compose.example.yml for the complete configuration template.

    For example, current Codex and Claude Code clients can use browser OAuth without storing a

    CodeAlive API key:

    bash
    codex mcp add codealive --url https://mcp.codealive.ai/api
    codex mcp login codealive
    
    claude mcp add --transport http codealive https://mcp.codealive.ai/api
    # Start Claude Code and run /mcp to authenticate.

    Cursor and OpenCode also discover OAuth automatically from the same URL. Use

    cursor-agent mcp login codealive or opencode mcp auth codealive when their UI does not prompt

    automatically. API-key configuration remains available as a compatibility option.

    OAuth 2.1 deployment profile

    Remote HTTP deployments can enable browser authorization while keeping legacy API-key clients

    working during rollout. OAuth mode publishes MCP Protected Resource Metadata, validates exact

    issuer/resource-bound JWTs, and exchanges them for a separate short-lived Tool API token. The

    incoming MCP bearer token is never forwarded downstream.

    Environment variablePurpose
    CODEALIVE_MCP_OAUTH_ENABLED=trueEnables OAuth validation and MCP authorization discovery for HTTP transport
    CODEALIVE_OAUTH_ISSUERExact OpenIddict issuer, with a trailing slash
    CODEALIVE_MCP_RESOURCEExact public MCP resource URL; its path is also the HTTP MCP path
    CODEALIVE_TOOL_API_RESOURCEDownstream audience; defaults to urn:codealive:tool-api
    CODEALIVE_OAUTH_INTERNAL_CLIENT_IDConfidential resource-server client used only for token exchange
    CODEALIVE_OAUTH_INTERNAL_CLIENT_SECRETRequired secret for that internal client; startup fails closed when it is missing

    The authorization server and MCP service values must match exactly. In CodeAlive Web.Server the

    corresponding settings live under McpOAuth (Enabled, Issuer, Resource,

    ToolApiResource, InternalClientId, and InternalClientSecret). Persist the Web.Server Data

    Protection key ring and OpenIddict signing/encryption certificates across replicas and restarts.

    For a zero-downtime internal credential rotation, give the new credential a new client ID, deploy

    Web.Server with both current and PreviousInternalClientId/PreviousInternalClientSecret, roll

    MCP replicas to the new current pair, then remove the previous pair. Web.Server deliberately fails

    startup instead of changing a secret in place under an existing client ID.

    Enable the Web.Server and MCP flags in the same rollout; a half-enabled deployment is not a valid

    steady state. API-key credentials retain their explicit legacy grammar and are never used as a

    fallback after OAuth validation fails.

    Connecting MCP Clients to Your Deployed Instance

    Use the same generic connection details as CodeAlive Cloud, replacing the endpoint with your deployment's /api URL:

    • Endpoint: https://your-server.example.com/api
    • Transport: Streamable HTTP
    • Authentication header: Authorization: Bearer YOUR_API_KEY_HERE

    For the exact configuration format, open the relevant client integration guide.

    🪟 Windows & WSL

    Use the client-specific documentation for Windows and WSL setup:

    • Claude Code
    • Claude Desktop
    • All MCP integration guides
    • Troubleshooting

    For self-hosted servers running in WSL2, Windows clients must be able to reach the server's /api endpoint. Use mirrored networking on supported Windows 11 versions or connect through the WSL2 VM address.

    🐞 Troubleshooting

    Quick Diagnostics

    1. Test the hosted service:

    bash
    curl https://mcp.codealive.ai/health

    2. Check your API key:

    bash
    curl -H "Authorization: Bearer YOUR_API_KEY" https://app.codealive.ai/api/v1/data_sources

    3. Enable debug logging: Add --debug to local server args

    Common Issues

    • "Connection refused" → Check internet connection
    • "401 Unauthorized" → Verify your API key
    • "No repositories found" → Check API key permissions in CodeAlive dashboard
    • Client-specific logs → See your AI client's documentation for MCP logs

    Windows / WSL Issues

    • **docker: command not found in WSL** → Enable Docker Desktop WSL integration for your distro (Settings → Resources → WSL integration), or use the full path /usr/bin/docker
    • **ENOENT or spawn error for npx/python** → Non-interactive WSL shells don't inherit nvm/pyenv paths. Use absolute paths in MCP configs
    • **Connection refused to self-hosted server in WSL2** → WSL2 uses NAT networking; localhost differs between Windows and WSL2. Enable mirrored networking in .wslconfig or use the WSL2 VM IP (hostname -I)
    • Claude Desktop can't connect to WSL MCP server → Claude Desktop doesn't support WSL subprocess spawning. Use Remote HTTP (https://mcp.codealive.ai/api), Docker Desktop, or the wsl.exe proxy pattern (see Windows & WSL section)

    Getting Help

    • 📧 Email: support@codealive.ai
    • 🐛 Issues: GitHub Issues

    ---

    📦 Publishing to MCP Registry

    For maintainers: see DEPLOYMENT.md for instructions on publishing new versions to the MCP Registry.

    ---

    Privacy Policy

    CodeAlive processes the repositories and queries you send through this extension in order to provide semantic search and codebase analysis. For complete privacy details, see CodeAlive Privacy Policy.

    ---

    📄 License

    MIT License - see LICENSE file for details.

    ---

    Ready to supercharge your AI assistant with deep code understanding?

    Get started now →

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