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paiml-mcp-agent-toolkit MCP Server

paiml/paiml-mcp-agent-toolkit

Score: 85.6 ↑ 0.9% Rank #818 Agent Framework
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Pragmatic AI Labs MCP Agent Toolkit - An MCP Server designed to make code with agents more deterministic

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Overview

paiml/paiml-mcp-agent-toolkit is a Rust MCP server licensed under MIT. Pragmatic AI Labs MCP Agent Toolkit - An MCP Server designed to make code with agents more deterministic Topics: agentic, c, deno, kotlin, mcp, mcp-server, paiml, pmcp, python, rust, toolkit, typescript, ruchy, paiml-active-tool.

Ranked #818 out of 24846 indexed tools.

In the top 4% of all indexed tools.

Ecosystem

Rust MIT
agenticcdenokotlinmcpmcp-serverpaimlpmcppythonrusttoolkittypescriptruchypaiml-active-tool

Score Breakdown

StarsFreshnessIssue HealthContributorsDependents
Stars 15% 165

165 stars → growing community

Freshness 25% 16d ago

Last commit 16d ago → recently updated

Issue Health 25% 83%

743/892 issues closed → responsive maintainer

Contributors 10% 8

8 contributors → small team

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A
PyPI Downloads N/A
Forks 30
Description Good
License MIT

Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →

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AgentRank score for paiml/paiml-mcp-agent-toolkit
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Matched Queries

"mcp server""mcp-server""agent tool"topic:mcptopic:mcp-server

From the README

<h1 align="center">PMAT</h1>

<p align="center">
  
</p>

<p align="center">
  <strong>Zero-configuration AI context generation for any codebase</strong>
</p>

<div align="center">

[Installation](#installation) | [MCP Server](#mcp-server) | [Usage](#usage) | [Features](#features) | [Examples](#examples) | [Documentation](https://paiml.github.io/pmat-book/)

</div>

---

## Table of Contents

- [What is PMAT?](#what-is-pmat)
- [Installation](#installation)
- [MCP Server](#mcp-server)
- [Usage](#usage)
- [Features](#features)
- [Architecture](#architecture)

## What is PMAT?

**PMAT** (Pragmatic Multi-language Agent Toolkit) provides everything needed to analyze code quality and generate AI-ready context:

- **Context Generation** - Deep analysis for Claude, GPT, and other LLMs
- **Technical Debt Grading** - A+ through F scoring with 6 orthogonal metrics
- **Mutation Testing** - Test suite quality validation (85%+ kill rate)
- **Repository Scoring** - Quantitative health assessment (0-2
Read full README on GitHub →

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