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mcp-llm

mcp-llm

by sammcj
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

MCP LLM

An MCP server that provides access to LLMs using the LlamaIndexTS library.

I put some LLMs in your MCP for your LLMs

Features

This MCP server provides the following tools:

  • generate_code: Generate code based on a description

  • generate_code_to_file: Generate code and write it directly to a file at a specific line number

  • generate_documentation: Generate documentation for code

  • ask_question: Ask a question to the LLM

call a llm to generate code call a reasoning llm to write some documentation

Related MCP server: Globalping

Installation

Installing via Smithery

To install LLM Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @sammcj/mcp-llm --client claude

Manual Install From Source

  1. Clone the repository

  2. Install dependencies:

npm install

  1. Build the project:

npm run build

  1. Update your MCP configuration

Using the Example Script

The repository includes an example script that demonstrates how to use the MCP server programmatically:

node examples/use-mcp-server.js

This script starts the MCP server and sends requests to it using curl commands.

Examples

Generate Code

{
  "description": "Create a function that calculates the factorial of a number",
  "language": "JavaScript"
}

Generate Code to File

{
  "description": "Create a function that calculates the factorial of a number",
  "language": "JavaScript",
  "filePath": "/path/to/factorial.js",
  "lineNumber": 10,
  "replaceLines": 0
}

The generate_code_to_file tool supports both relative and absolute file paths. If a relative path is provided, it will be resolved relative to the current working directory of the MCP server.

Generate Documentation

{
  "code": "function factorial(n) {\n  if (n <= 1) return 1;\n  return n * factorial(n - 1);\n}",
  "language": "JavaScript",
  "format": "JSDoc"
}

Ask Question

{
  "question": "What is the difference between var, let, and const in JavaScript?",
  "context": "I'm a beginner learning JavaScript and confused about variable declarations."
}

License

Available Tools

4 tools
ask_questionC

Ask a question to the LLM

Inputs: question (required), context.

generate_codeC

Generate code based on a description

Inputs: description (required), language, additionalContext.

generate_code_to_fileB

Generate code and write it directly to a file at a specific line number

Inputs: description (required), filePath (required), lineNumber (required), language, +2 more.

generate_documentationC

Generate documentation for code

Inputs: code (required), language, format.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    B3/5.0

    Scored across 4 tools

    Disambiguation3/5

    The tools have overlapping purposes that could cause confusion. 'generate_code' and 'generate_code_to_file' both generate code, with the latter adding file writing functionality, which might lead to misselection when file output isn't needed. However, 'ask_question' and 'generate_documentation' are more distinct in their purposes, helping to mitigate some ambiguity.

    Naming Consistency4/5

    The naming follows a consistent verb_noun pattern throughout, such as 'ask_question' and 'generate_documentation'. There is a minor deviation with 'generate_code_to_file', which includes a prepositional phrase, but overall the pattern is clear and readable, maintaining good consistency.

    Tool Count4/5

    With 4 tools, the count is slightly low but reasonable for an LLM-focused server. It covers core functionalities like questioning, code generation, and documentation, though it might feel thin if more advanced features are expected. The scope is well-defined, so the number is appropriate for basic operations.

    Completeness3/5

    There are notable gaps in the tool surface for an LLM domain. While it covers code generation and documentation, it lacks tools for editing, refactoring, or analyzing existing code, and there's no way to manage conversations or context. This could lead to agent failures in more complex workflows, but core tasks are addressed.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

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