# MCP Reasoner

> Use this tool when you need to systematically reason through complex problems and make informed decisions. The MCP Reasoner solves challenges requiring probabilistic reasoning and decision-making under uncertainty, leveraging Beam Search and Monte Carlo Tree Search algorithms. It takes in problem definitions and outputs optimized solutions, ideal for use cases involving uncertain or dynamic environments.

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

## Description

A systematic reasoning MCP server for Claude Desktop, featuring Beam Search and Monte Carlo Tree Search to facilitate complex problem-solving and decision-making processes.

## Trust

- **Trust score (0–1):** 0.93
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/pz4pgwvn1c)
- **Repository:** <https://github.com/parmarjh/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": "parmarjh-mcp-reasoner"
    }
  }
}
```

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