AI-Parrot MCP Server

This repository hosts Model Context Protocol (MCP) server configurations using ai-parrot. It allows you to expose various ai-parrot tools (or custom functions) as MCP-compliant servers that can be consumed by AI agents and clients (like Claude Desktop, Antigravity, etc.).

Quick Start

Installation:

# Install uv
curl -LsSf https://astral.sh/uv/install.sh | sh

# Create virtual environment
uv venv --python 3.11 .venv

# Activate virtual environment
source .venv/bin/activate

# Install dependencies
uv sync

# or manually install ai-parrot:
uv pip install ai-parrot[mcp,llms]

Create the environment file:

mkdir env
kardex create

This creates the entire NavConfig project structure at parrot-mcp-server (environment: dev)

Creating a New Configuration

1. create a directory mcp_servers
2. Create a new file in mcp_servers/ (e.g., server.yaml).
3. Add the MCPServer block.
4. List the tools you want to expose.

Example: Google Search Server

MCPServer:
  name: GoogleMCP
  port: 8082
  transport: http
  tools:
    - GoogleSearch:
        api_key: GOOGLE_API_KEY
        cse_id: GOOGLE_CSE_ID

Run the MCP server:

parrot mcp --config mcp_servers/server.yaml

Configuration

Servers are configured using YAML files located in the mcp_servers/ directory.

Structure

A configuration file defines a single MCPServer block:

MCPServer:
  name: MyServer               # Friendly name
  host: 0.0.0.0                # Host to bind to
  port: 8081                   # Port to listen on
  transport: http              # 'http' or 'stdio'
  auth_method: api_key         # 'none' or 'api_key'
  api_key: MY_ENV_API_KEY      # API Key (can be environment variable)
  tools:
    - ToolName:                # Class name of the tool/toolkit
        arg1: value            # Arguments passed to __init__
        arg2: ENV_VAR_NAME     # Environment variable substitution

Key Attributes

• transport:
  • http: Starts a web server (useful for remote access).
  • stdio: Uses standard input/output (useful for local integration with Claude Desktop).
  • sse: Starts a web server with Server-Sent Events (useful for remote access).
  • ws: Starts a web server with WebSocket (useful for remote access).
  • quic: Starts a web server with QUIC (useful for remote access).
  • grpc: Starts a web server with gRPC (useful for remote access).
  • unix: Starts a web server with Unix domain sockets (useful for local integration with Claude Desktop).
• auth_method:
  • none: No authentication required.
  • api_key: Requires X-API-Key header.
• api_key:
  • Sets the required API key when auth_method is api_key.
  • Environment Substitution: If the value checks an environment variable (e.g., MCP_SERVER_API_KEY), it will be used.
• tools:
  • A list of tools to load. Each entry is a dictionary where the key is the Tool/Toolkit class name (from ai-parrot) and the value is a dictionary of arguments.

Environment Variable Substitution

You can use environment variables for any string value in the configuration (Server args or Tool args).

• If a value matches an existing environment variable name, it is replaced by that variable's value.
• Example: "server_url": "JIRA_URL" -> resolves to os.getenv("JIRA_URL").

Read the AI-Parrot documentation for more information.

Available Tools

Any tool available in ai-parrot can be loaded. Common tools include:

• JiraToolkit: Operations for Jira (Get, Search, Transition issues).
• GoogleSearch: Perform Google searches.
• OpenWeather: Get weather data.
• ArangoDBSearch: Search ArangoDB.
• PostgreSQLToolkit / DatabaseQuery: SQL database interactions.
• GitToolkit: Git repository operations.
• AWSCloudWatch: AWS CloudWatch logs and metrics.
• MsTeams: Microsoft Teams inte

... View full README on GitHub