agentleFS
ishandutta2007ishandutta2007/Awesome-Agent-Skills/skills/mcp-tool-integration/SKILL.md

mcp-tool-integration

Skill21 starsChanged 5 months agoMITView on GitHub

Implementing and connecting Model Context Protocol (MCP) tools. Use when you need to extend an agent's capabilities with external data sources or execution environments.

The file

We split this skill into the rules it gives an agent

5 rules. About 0 are common, 5 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈5

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Design Tool Schemas: Create clear, descriptive JSON schemas for tool inputs.

    line 18
  2. Distinctive:

    Implement Handlers: Write the execution logic.

    line 19
  3. Distinctive:

    Test Locally: Verify tool execution and error handling.

    line 20
  4. Distinctive:

    Configure Client: Add the MCP server to the agent's configuration file.

    line 21
  5. Distinctive:

    No local client invocation has been tested

    line 36

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

MCP Tool Integration

Overview

Model Context Protocol (MCP) is the standard for connecting AI agents to external tools and context. This skill guides the integration and development of new MCP tools.

When to Use

  • You need to access data outside the agent's current context
  • You are building custom tools for Claude Desktop or other MCP-compatible clients
  • Integrating REST APIs, databases, or local services via MCP

Process

  1. Define the Protocol: Choose standard stdio or SSE depending on the deployment environment.
  2. Design Tool Schemas: Create clear, descriptive JSON schemas for tool inputs.
  3. Implement Handlers: Write the execution logic.
  4. Test Locally: Verify tool execution and error handling.
  5. Configure Client: Add the MCP server to the agent's configuration file.

Common Rationalizations

RationalizationWhy It Is Wrong
"The handler works, so the tool is done."Agents rely on schemas, names, and descriptions as much as handler code.
"Errors can just throw."MCP clients need predictable errors so agents can recover or explain the failure.
"The client config is obvious."A working server is not useful until the target client can discover and invoke it.

Red Flags

  • Tool names or descriptions are vague
  • Inputs accept broad strings instead of structured fields
  • The handler returns raw internal errors or stack traces
  • No local client invocation has been tested

Verification

Before finishing, confirm:

  • Tool schemas describe the inputs an agent should actually provide
  • Handler success and error paths were exercised locally
  • Client configuration is documented and tested
  • Secrets, tokens, and local paths are not exposed in tool responses

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.