# mcp-reasoner

> Use this tool when you need to systematically evaluate thoughts and generate reasoned responses, leveraging beam search capabilities to optimize output. The mcp-reasoner server implementation solves problems related to automated reasoning and decision-making, particularly in applications requiring thoughtful and informed responses. It accepts input queries and produces evaluated responses as output, making it suitable for use cases involving complex thought processes and idea generation.

Canonical page: https://skillsregistry.net/skills/jacck-mcp-reasoner  
JSON: https://api.skillsregistry.net/v1/skills/jacck-mcp-reasoner

## Description

A systematic reasoning MCP server implementation for Claude Desktop with beam search and thought evaluation capabilities

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-09-02

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/g71nwrrr8e)
- **Repository:** <https://github.com/Jacck/mcp-reasoner>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "jacck-mcp-reasoner"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/jacck-mcp-reasoner` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/jacck-mcp-reasoner/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt