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Manticore Search

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MCP server for Manticore Search — query and manage search database

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#database#git#monitoring#memory

Manticore Search MCP Server

PyPI - Version uv

MCP server for Manticore Search — enables AI assistants to query and manage Manticore Search databases directly.

What It Does

Tools

ToolDescription
run_queryExecute SQL queries (SELECT, SHOW, DESCRIBE, etc.)
list_tablesList all tables and indexes
describe_tableGet table schema
list_documentationList available documentation files
get_documentationFetch specific documentation from Manticore manual

Prompts

  • manticore_initial_prompt — Built-in prompt teaching LLMs about Manticore Search features (full-text operators, KNN vector search, fuzzy search, etc.)

Health Check

HTTP endpoint at /health for monitoring connectivity.

Connect to Your AI Assistant

<details> <summary><strong>Claude Code</strong></summary>

Open terminal and run:

claude mcp add manticore -- uvx mcp-manticore

Or with environment variables:

claude mcp add manticore -- uvx mcp-manticore -- \
  MANTICORE_HOST=localhost \
  MANTICORE_PORT=9308

For full configuration, edit ~/.claude/mcp_settings.json:

{
  "mcpServers": {
    "manticore": {
      "command": "uvx",
      "args": ["mcp-manticore"],
      "env": {
        "MANTICORE_HOST": "localhost",
        "MANTICORE_PORT": "9308"
      }
    }
  }
}

Restart Claude Code or type /mcp restart to apply changes.

</details> <details> <summary><strong>Cursor</strong></summary>

Method 1: Via Settings UI

  1. Open Cursor → Settings → Tools & MCP
  2. Click "Add MCP Server"
  3. Enter name: manticore
  4. Command: uvx mcp-manticore

Method 2: Via Config File

Global config (~/.cursor/mcp.json):

{
  "mcpServers": {
    "manticore": {
      "command": "uvx",
      "args": ["mcp-manticore"],
      "env": {
        "MANTICORE_HOST": "localhost",
        "MANTICORE_PORT": "9308"
      }
    }
  }
}

Project config (.cursor/mcp.json in your project):

{
  "mcpServers": {
    "manticore": {
      "command": "uvx",
      "args": ["mcp-manticore"]
    }
  }
}
</details> <details> <summary><strong>Windsurf</strong></summary>

Method 1: Via Cascade UI

  1. Open Windsurf → Cascade panel
  2. Click the MCPs icon (🔨) in the top-right
  3. Click "Add Server"
  4. Enter: uvx mcp-manticore

Method 2: Via Config File

Edit ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "manticore": {
      "command": "uvx",
      "args": ["mcp-manticore"],
      "env": {
        "MANTICORE_HOST": "localhost",
        "MANTICORE_PORT": "9308"
      }
    }
  }
}

Or open directly in Windsurf: Cmd/Ctrl + Shift + P → "MCP Configuration Panel"

</details> <details> <summary><strong>OpenAI Codex</strong></summary>

Run in terminal:

codex mcp add manticore -- uvx mcp-manticore

With environment variables:

codex mcp add manticore \
  --env MANTICORE_HOST=localhost \
  --env MANTICORE_PORT=9308 \
  -- uvx mcp-manticore

Or edit ~/.codex/config.toml directly:

[mcp_servers.manticore]
command = "uvx"
args = ["mcp-manticore"]
env = { MANTICORE_HOST = "localhost", MANTICORE_PORT = "9308" }
</details> <details> <summary><strong>Gemini CLI</strong></summary>

Edit ~/.gemini/settings.json:

{
  "mcpServers": {
    "manticore": {
      "command": "uvx",
      "args": ["mcp-manticore"],
      "env": {
        "MANTICORE_HOST": "localhost",
        "MANTICORE_PORT": "9308"
      }
    }
  }
}
</details> <details> <summary><strong>VS Code (GitHub Copilot)</strong></summary>

Create .vscode/mcp.json in your workspace:

{
  "servers": {
    "manticore": {
      "type": "stdio",
      "command": "uvx",
      "args": ["mcp-manticore"],
      "env": {
        "MANTICORE_HOST": "localhost",
        "MANTICORE_PORT": "9308"
      }
    }
  }
}
</details> <details> <summary><strong>Cline</strong></summary>
  1. Open Cline panel in VS Code
  2. Click the MCP Servers icon
  3. Click "Configure" → "Add Server"
  4. Select "Command (stdio)" and enter:
    • Name: manticore
    • Command: uvx mcp-manticore

Or edit the MCP settings file directly (accessible via the MCP Servers icon → "Edit Config"):

{
  "mcpServers": {
    "manticore": {
      "command": "uvx",
      "args": ["mcp-manticore"],
      "env": {
        "MANTICORE_HOST": "localhost",
        "MANTICORE_PORT": "9308"
      }
    }
  }
}
</details> <details> <summary><strong>Roo Code</strong></summary>
  1. Open Roo Code panel in VS Code
  2. Click the MCP Servers icon → "Edit MCP Settings"
  3. Add the server configuration

Or create .roo/mcp.json in your project root:

{
  "mcpServers": {
    "manticore": {
      "command": "uvx",
      "args": ["mcp-manticore"],
      "env": {
        "MANTICORE_HOST": "localhost",
        "MANTICORE_PORT": "9308"
      }
    }
  }
}
</details> <details> <summary><strong>Claude Desktop (Legacy)</strong></summary>

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%/Claude/claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "manticore": {
      "command": "uvx",
      "args": ["mcp-manticore"],
      "env": {
        "MANTICORE_HOST": "localhost",
        "MANTICORE_PORT": "9308"
      }
    }
  }
}
</details>

HTTP Transport (Remote MCP)

By default, MCP uses stdio (local). For remote access:

export MANTICORE_MCP_SERVER_TRANSPORT=http
export MANTICORE_MCP_BIND_PORT=8000
export MANTICORE_MCP_AUTH_TOKEN="your-secure-token"

uvx mcp-manticore

Connect via URL:

{
  "mcpServers": {
    "manticore": {
      "url": "http://localhost:8000/mcp",
      "headers": {
        "Authorization": "Bearer your-secure-token"
      }
    }
  }
}

Development

# Clone and setup
git clone https://github.com/manticoresoftware/mcp-manticore.git
cd mcp-manticore

# Install dependencies
uv sync

# Run locally
uv run mcp-manticore

# Run with custom config
MANTICORE_HOST=remote-server MANTICORE_PORT=9308 uv run mcp-manticore

# Run tests
uv run pytest

# Build package
uv build

# Publish to PyPI
uv publish

Architecture

FilePurpose
mcp_manticore/mcp_env.pyConfiguration management
mcp_manticore/mcp_server.pyMCP server implementation
mcp_manticore/manticore_prompt.pyLLM guidance/prompts
mcp_manticore/docs_fetcher.pyGitHub docs fetcher
mcp_manticore/main.pyCLI entry point