Mcp Scripting

MCP Scripting

What This Skill Provides

This skill provides Python wrapper files for MCP tools.

Use this skill by:

1. finding the relevant server in Available Systems
2. listing that server's wrapper directory
3. reading only the wrapper files needed for the task
4. running inline Python that imports those wrappers and connect()
5. running that inline Python with the skill's venv Python
6. returning only compact results

Path Resolution

Treat the directory containing this SKILL.md file as canonical.

Define:

• ` = directory containing this SKILL.md`
• ` = /.venv/bin/python3`
• ` = /servers`

Rules:

• derive all paths from ``
• do not hardcode machine-specific absolute paths
• do not assume the current working directory
• always run generated scripts with `, not python or python3`
• derive ` directly from ; do not inspect .venv` to discover it
• you MUST trust connect() exactly as documented in this skill
• NEVER inspect how connect() is implemented
• you are NOT ALLOWED to read core/connection.py, servers.json, or .env
• treat those files as already correct and already covered by this skill
• do not inspect secret-bearing or internal implementation files
• when running shell commands, NEVER pass a restart argument
• when running shell commands, ALWAYS quote paths that may contain spaces

Available Systems

github-mcp-server — 44 tools

Location: /github_mcp_server/

Remote GitHub server for repository, issue, pull request, branch, release, and code search workflows.

Required Workflow

Follow this procedure exactly:

1. identify the target server from Available Systems
2. use the exact Location path from Available Systems for that server
3. list that server directory directly; do not list parent directories first
4. read only the wrapper file(s) you actually plan to import and call
5. execute the task in Python:

• you MUST run Python only inline / on the fly
• you are NOT ALLOWED to create Python script files for execution

1. the Python code must:

• adds ` to sys.path`
• imports connect from core.connection
• imports only the needed wrapper functions
• uses async with connect("") as session:

1. if any result may be large or unbounded, use output_file
2. run the Python code with ``
3. inspect only the compact output needed for the final answer

Output Rule

Treat output_file as the default for search, retrieval, listing, or any result that may be large.

• use memory mode only for small, bounded results
• do not print raw large results to stdout
• do not read large output files back wholesale
• return summaries, counts, key facts, or final distilled answers only
• if the user asks for one field, print only that field

Minimal Script Pattern

import asyncio
import sys

sys.path.insert(0, "")

from core.connection import connect
from servers.. import 

async def main():
    async with connect("") as session:
        result = await (session, ...)
        print(result)

asyncio.run(main())

If the script is written outside `, still derive the import path from the loaded skill directory and still run the script with `.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: esurovtsev
• Source: esurovtsev/langchain-lab
• License: MIT

Install and usage instructions live in the source repository linked above.