Server data from the Official MCP Registry
Summarize URLs, repurpose content, daily news digests, find competitors. Cost telemetry built in.
Summarize URLs, repurpose content, daily news digests, find competitors. Cost telemetry built in.
Remote endpoints: streamable-http: https://mcp-automations.fly.dev/mcp
A well-structured MCP server with proper error handling, reasonable authentication patterns, and appropriate permissions matching its purpose. Code quality is good with strict linting and testing. Minor concerns around broad exception handling in Tavily client and lenient JSON parsing do not significantly impact the overall security posture. Supply chain analysis found 5 known vulnerabilities in dependencies (0 critical, 3 high severity).
8 files analyzed · 9 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
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Available as Local & Remote
This plugin can run on your machine or connect to a hosted endpoint. during install.
From the project's GitHub README.
A production-grade Model Context Protocol server in Python — four LLM-callable tools, two transports, deployed two different ways.
| URL | |
|---|---|
| Source | https://github.com/wzltmp/mcp-automations |
| Playground (browser demo) | https://mcp-automations-5vgea2ynuyrvbzkcxm6yoh.streamlit.app/ |
| MCP HTTP server | https://mcp-automations.fly.dev/mcp |
# 30-second proof the server is up:
curl -X POST https://mcp-automations.fly.dev/mcp \
-H 'Content-Type: application/json' \
-H 'Accept: application/json, text/event-stream' \
-d '{"jsonrpc":"2.0","method":"initialize","id":1,
"params":{"protocolVersion":"2024-11-05",
"capabilities":{},
"clientInfo":{"name":"curl","version":"1"}}}'
Most "AI engineer" portfolio projects are applications (a RAG chatbot, an agent that does research). This project is the layer underneath — the typed tools an LLM can call and the transport plumbing that exposes them. MCP is the emerging standard for LLM tool use (~97M monthly SDK downloads as of early 2026); building one — not just consuming one — is the rare skill.
For a deeper look at the design decisions — why two transports, how cost telemetry works, the exception hierarchy, what I'd do differently — see WRITEUP.md.
| Tool | Model | What it does |
|---|---|---|
summarize_url(url, n_bullets) | Haiku 4.5 | Fetch a page, extract clean text with trafilatura, return an N-bullet summary |
repurpose_content(text, format) | Sonnet 4.6 | Turn long-form text into a twitter thread, linkedin post, or newsletter |
daily_digest(topic, n_results) | Haiku 4.5 | Tavily news search + ~200-word digest with citations |
find_competitors(domain, n) | Sonnet 4.6 | Identify N plausible competitors for a company by domain |
Plus one MCP resource (automations://catalog) and one MCP prompt (daily_brief) — using all three MCP primitives, not just tools.
Every tool returns a typed Pydantic model with per-call token usage and dollar cost attached. Cheap tasks route to Haiku 4.5 ($1/M in, $5/M out), writing-heavy tasks to Sonnet 4.6 ($3/M in, $15/M out).
Add one of these to ~/Library/Application Support/Claude/claude_desktop_config.json (Mac) or %APPDATA%/Claude/claude_desktop_config.json (Windows), then restart Claude Desktop.
Option A — local stdio (no network, runs the server as a subprocess):
{
"mcpServers": {
"mcp-automations": {
"command": "python",
"args": ["-m", "mcp_server.server"],
"cwd": "/absolute/path/to/mcp-automations",
"env": {
"ANTHROPIC_API_KEY": "sk-ant-...",
"TAVILY_API_KEY": "tvly-..."
}
}
}
}
Option B — remote HTTP (talks to the live Fly server, no local setup):
{
"mcpServers": {
"mcp-automations": {
"url": "https://mcp-automations.fly.dev/mcp",
"transport": "http"
}
}
}
Then ask Claude something like "summarize https://www.paulgraham.com/greatwork.html in 3 bullets" — it'll call summarize_url automatically.
pip install -r requirements.txt
# Stdio (for Claude Desktop):
python -m mcp_server.server
# HTTP server (defaults to 0.0.0.0:8765):
MCP_TRANSPORT=http python -m mcp_server.server
# Streamlit playground:
streamlit run playground/app.py
Requires Python 3.13. Needs ANTHROPIC_API_KEY and TAVILY_API_KEY in .env (see .env.example).
┌────────────────┐ stdio ┌──────────────────────┐
│ Claude Desktop ├───────────────►│ │
└────────────────┘ │ │
│ mcp_server/ │
┌────────────────┐ HTTP/JSON │ server.py │
│ Remote client ├───────────────►│ (FastMCP) │
└────────────────┘ (Fly.io) │ │
│ 4 tools │
┌────────────────┐ direct call │ 1 resource │
│ Streamlit UI ├───────────────►│ 1 prompt │
└────────────────┘ └──────────┬───────────┘
│
┌──────────┴───────────┐
│ Anthropic + Tavily │
│ (lazy clients) │
└──────────────────────┘
The same Python callables back all three entry points. The transport is just a wrapper.
mcp-automations/
├── mcp_server/
│ ├── server.py # FastMCP server: 4 tools + 1 resource + 1 prompt
│ ├── models.py # Pydantic I/O schemas (incl. per-call Cost telemetry)
│ └── exceptions.py # MCPToolError + UpstreamAPIError / EmptyLLMResponseError / ExtractionError
├── playground/
│ └── app.py # Streamlit UI with per-session call + spend caps
├── tests/ # offline unit tests (httpx/anthropic/tavily all mocked)
├── Dockerfile # python:3.13-slim, MCP_TRANSPORT=http for Fly
├── fly.toml # shared-cpu-1x, 256mb, auto-stop when idle
└── .github/workflows/ # ruff + strict mypy + pytest on every push
models.Cost) — token counts and USD attached so a client doesn't have to re-derive it.UpstreamAPIError, EmptyLLMResponseError, ExtractionError each route differently in logs and the Streamlit UI.MCP_TRANSPORT=stdio|http env switch; HTTP host/port from env so the same image runs on Fly..github/workflows/ci.yml).MCP is transport-agnostic, so one server serves both a local Claude Desktop user (stdio subprocess) and a hosted multi-tenant deployment (HTTPS). It also exposes three primitives that most demos skip:
automations://catalog returns the tool list as JSON)daily_brief chains daily_digest + repurpose_content)Using all three is a signal of reading the spec, not just a quickstart.
✅ Code on GitHub, CI green
✅ Public playground on Streamlit Cloud
✅ Public MCP HTTP server on Fly.io
✅ Cost protection (per-session caps + monthly Anthropic cap)
✅ Real test coverage (23 offline unit tests)
✅ Listed on the Official MCP Registry as io.github.wzltmp/mcp-automations
✅ Long-form writeup of design decisions
🚧 Demo gif + screenshots (planned)
🚧 n8n self-host via docker-compose (planned)
MIT.
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