mcp-template
A batteries-included Python template that ships a shared service registry as a CLI, MCP server, and HTTP API, enabling rapid development of MCP tools like the included Gmail skill.
README
custom-mcps
<p align="center"> <img src="media/banner.png" alt="2" width="400"> </p>
<p align="center"> <b>Custom MCPs for a wide range of applications.</b><br> Write an integration once in <code>services/</code> and it ships three ways: a CLI, an MCP server (streamable HTTP at <code>/mcp</code>), and an HTTP API, all over one shared service registry. Gmail is the first. </p>
<p align="center"> <a href="#key-features">Key Features</a> • <a href="#architecture">Architecture</a> • <a href="#quick-start">Quick Start</a> • <a href="#cli-usage">CLI Usage</a> • <a href="#adding-commands">Adding Commands</a> • <a href="#configuration">Configuration</a> • <a href="manual_docs/deploy.md">Deploy</a> • <a href="#credits">Credits</a> </p>
<p align="center"> <a href="https://railway.com/deploy/gmailmcp"><img alt="Deploy on Railway" src="https://railway.com/button.svg" height="32"></a> <a href="https://render.com/deploy?repo=https://github.com/Edison-Watch/Custom-MCPs"><img alt="Deploy to Render" src="https://render.com/images/deploy-to-render-button.svg" height="32"></a> </p>
<p align="center"> <img alt="Project Version" src="https://img.shields.io/badge/dynamic/toml?url=https%3A%2F%2Fraw.githubusercontent.com%2FEdison-Watch%2FCustom-MCPs%2Fmain%2Fpyproject.toml&query=%24.project.version&label=version&color=blue"> <img alt="Python Version" src="https://img.shields.io/badge/dynamic/toml?url=https%3A%2F%2Fraw.githubusercontent.com%2FEdison-Watch%2FCustom-MCPs%2Fmain%2Fpyproject.toml&query=%24.project['requires-python']&label=python&logo=python&color=blue"> <img alt="GitHub repo size" src="https://img.shields.io/github/repo-size/Edison-Watch/Custom-MCPs"> <img alt="GitHub Actions Workflow Status" src="https://img.shields.io/github/actions/workflow/status/Edison-Watch/Custom-MCPs/a_test_target_tests.yml?branch=main"> <a href="https://skills.sh/Edison-Watch/Custom-MCPs"><img alt="skills.sh" src="https://skills.sh/b/Edison-Watch/Custom-MCPs"></a>
</p>
Agent Prompt
Copy and paste this into your AI coding agent (Claude Code, Cursor, Copilot, etc.) to install:
Install the CLI and download the gmail-mcp skill:
uv tool install custom-mcps
curl -fsSL https://raw.githubusercontent.com/Edison-Watch/Custom-MCPs/main/scripts/install-skills.sh -o install-skills.sh
bash install-skills.sh && rm install-skills.sh
The official gmail-mcp agent skill is self-published on skills.sh. Install it directly with:
npx skills add Edison-Watch/Custom-MCPs
The skill's source of truth lives in skills/gmail-mcp/SKILL.md;
make sync-skills mirrors it to the landing page's
/.well-known/agent-skills/ discovery tree (digest-pinned in index.json).
App Distribution
- MCP server with OAuth
- Claude and ChatGPT connectors
- APIs and SDKs
- Chat interfaces like iMessage and WhatsApp
- A dashboard that uses the same MCP layer
- Open source
Key Features
| Feature | Stack |
|---|---|
| CLI (auto-discovery commands, global flags, shell completions, self-update) | Typer |
MCP server (streamable HTTP at /mcp, services auto-registered as tools; stdio supported for local dev) |
FastMCP |
HTTP API server (also hosts /mcp) |
FastAPI + Uvicorn |
| Auth | WorkOS + API keys |
| Payments | Stripe |
| Database + migrations | SQLAlchemy + Alembic |
Config (YAML + .env) |
Pydantic-settings |
| LLM inference + observability | DSPY + LiteLLM + LangFuse |
| Testing | pytest + TestTemplate |
| Lint / type / dead-code | Ruff + Vulture + ty + import-linter |
| Pre-commit (folder size, ai-writing, agent-config sync) | prek |
| Telemetry | Anonymous, opt-out |
Architecture
One codebase, three interfaces. Write business logic once in services/ and it ships as a CLI subcommand, an MCP tool, and an HTTP route - same Pydantic input/output contract everywhere.
┌──────────────┐ ┌──────────────┐ ┌──────────────┐
│ src/cli/app │ │ mcp_server/ │ │ api_server/ │ transport / interface
│ (Typer) │ │ (FastMCP) │ │ (FastAPI) │
└──────┬───────┘ └──────┬───────┘ └──────┬───────┘
│ │ │
└─────────────────┼─────────────────┘
▼
┌───────────────┐
│ services/ │ pure @service functions
│ @service │ (transport-agnostic)
└───────┬───────┘
▼
┌───────────────┐
│ models/ │ Pydantic I/O contracts
└───────┬───────┘
▼
┌────────────┬───────┬────────────┬─────────────┐
│ common/ │ db/ │ utils/llm/ │ src/utils/ │ shared infra
│ (config) │ (ORM) │ (DSPY) │ (logs/theme)│
└────────────┴───────┴────────────┴─────────────┘
MCP UI (optional)
Need elicitation, image output, or an iframe dashboard for an MCP tool? Add an opt-in enhancer in mcp_server/enhancers/. Enhancers wrap a service for the MCP transport only - the pure service stays untouched and CLI/API consumers are unaffected.
See mcp_server/MCP_UI_ARCHITECTURE.md for the full design.
Quick Start
uv sync # install deps
uv run edisonmcps --help # see all CLI commands
uv run edisonmcps greet Alice # run a command
uv run edisonmcps init my_command # scaffold a new command
uv run edisonmcps-serve # start the server (HTTP API + MCP at /mcp on one port)
uv run edisonmcps-mcp # legacy: stdio MCP only, for local Claude Desktop / dev
Deploy
One-click deploy to Railway or Render (backend + managed Postgres, migrations run automatically). See deployment docs for the per-platform setup, the Railway template variable map, and OAuth/secret wiring.
CLI Usage
Global flags go before the subcommand:
| Flag | Short | Description |
|---|---|---|
--verbose |
-v |
Increase output verbosity |
--quiet |
-q |
Suppress non-essential output |
--debug |
Show full tracebacks on error | |
--format |
-f |
Output format: table, json, plain |
--dry-run |
Preview actions without executing | |
--version |
-V |
Print version and exit |
uv run edisonmcps --format json config show # JSON output
uv run edisonmcps --dry-run greet Bob # preview without executing
uv run edisonmcps --verbose greet Alice # detailed output
Adding Commands
Drop a Python file in src/cli/commands/ and it is auto-discovered.
Single command - export a main() function:
# src/cli/commands/hello.py
from typing import Annotated
import typer
def main(name: Annotated[str, typer.Argument(help="Who to greet.")]) -> None:
"""Say hello."""
typer.echo(f"Hello, {name}!")
uv run edisonmcps hello World # Hello, World!
Subcommand group - export app = typer.Typer():
# src/cli/commands/db.py
import typer
app = typer.Typer()
@app.command()
def migrate() -> None:
"""Run migrations."""
...
uv run edisonmcps db migrate
Or scaffold with: uv run edisonmcps init my_command --desc "Does something".
Configuration
from common import global_config
# Access config values from common/global_config.yaml
global_config.example_parent.example_child
# Access secrets from .env
global_config.OPENAI_API_KEY
CLI config inspection:
uv run edisonmcps config show # full config
uv run edisonmcps config get llm_config.cache_enabled # single value
uv run edisonmcps config set logging.verbose false # write override
Credits
This software uses the following tools:
- Cursor: The AI Code Editor
- uv
- Typer: CLI framework
- Rich: Terminal formatting
- prek: Rust-based pre-commit framework
- DSPY: Pytorch for LLM Inference
- LangFuse: LLM Observability Tool
About the Core Contributors
<a href="https://github.com/Edison-Watch/Custom-MCPs/graphs/contributors"> <img src="https://contrib.rocks/image?repo=Edison-Watch/Custom-MCPs" /> </a>
Made with contrib.rocks.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.