Codealive MCP

Name: Codealive MCP
Author: CodeAlive-AI

by CodeAlive-AIversion 3.0.3i★ –iRuns on your computer

Registry nameio.github.CodeAlive-AI/codealive-mcp

Install

Overview

Description from the maker (original English)

Semantic code search and analysis from CodeAlive for AI assistants and agents.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory
You need to fill in: CODEALIVE_API_KEY

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: CODEALIVE_API_KEY

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

DockerDocker installed

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "codealive": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "CODEALIVE_API_KEY",
        "ghcr.io/codealive-ai/codealive-mcp:3.0.3"
      ],
      "env": {
        "CODEALIVE_API_KEY": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add codealive --env CODEALIVE_API_KEY=your-value -- docker run -i --rm -e CODEALIVE_API_KEY ghcr.io/codealive-ai/codealive-mcp:3.0.3

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "codealive": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "CODEALIVE_API_KEY",
        "ghcr.io/codealive-ai/codealive-mcp:3.0.3"
      ],
      "env": {
        "CODEALIVE_API_KEY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "codealive": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "CODEALIVE_API_KEY",
        "ghcr.io/codealive-ai/codealive-mcp:3.0.3"
      ],
      "env": {
        "CODEALIVE_API_KEY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

CODEALIVE_API_KEY secret required env
Your CodeAlive API key. Get one at https://app.codealive.ai/ under MCP & API.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account CodeAlive-AI, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 7226 servers in this category
Published to the registry more recently than 24% of the other 7226 servers in this category
Basic checks equal to or better than 100% of the other 7226 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Codealive MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: CODEALIVE_API_KEY

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (3.0.3) reached the registry 4 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated 3 days ago

Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 20 days ago

Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated 44 days ago

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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

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:

`get_data_sources` - List your indexed repositories and workspaces
`semantic_search` - Canonical semantic search across indexed artifacts
`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
`get_repository_ontology` - Get repository-level orientation for one selected repository
`get_file_tree` - Inspect a bounded file tree for one repository
`read_file` - Read a repository-relative file path, optionally with a line range
`fetch_artifacts` - Load the full source for relevant search hits (missing or inaccessible identifiers are reported back, not silently dropped)
`get_artifact_relationships` - Expand call graph, inheritance, and reference relationships for one artifact
`get_artifact_query_schema` - Inspect supported ArtifactQuery entities, fields, and examples
`query_artifact_metadata` - Run read-only metadata analytics across selected repositories
`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:

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:

/plugin marketplace add CodeAlive-AI/codealive-skills

/plugin install codealive@codealive-marketplace

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

Sign up at https://app.codealive.ai/
Navigate to MCP & API
Click "+ Create API Key"
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.

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

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.

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

Client	Setup guide
Claude Code	Claude Code
Claude Desktop	Claude Desktop
Cursor	Cursor
Visual Studio Code	VS Code
Windsurf	Windsurf
Cline	Cline
Continue	Continue
Codex	Codex
Gemini CLI	Gemini CLI
Amazon Q Developer	Amazon Q
OpenCode	OpenCode
SourceCraft Code Assistant and SourceCraft CLI	SourceCraft
Zed	Zed
ChatGPT	ChatGPT
OpenClaw	OpenClaw
KodaCode, GigaCode, Roo Code, Goose, Kilo Code, Qwen Code, Kiro, Qoder, JetBrains AI Assistant, n8n, and more	Other 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

# 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

# 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:

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:

# 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

🚢 HTTP Deployment (Self-Hosted & Cloud)

**Deploy the

Only the beginning is shown; read the rest in the repo

Codealive MCP

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

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

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

Setup with uv (recommended)

Or setup with pip

Local Server Configuration

Running HTTP Server Locally

Test health endpoint

Only for browser callers; ordinary MCP clients do not send Origin.

Testing Your Local Installation

Install the repository pre-push dependency audit once per clone

Quick smoke test (recommended)

Or run directly

With your API key for full testing

Run unit tests

Run all tests

Equivalent direct locked test run

🌐 Community Plugins

🚢 HTTP Deployment (Self-Hosted & Cloud)