# mcp-toolselect

> Use this tool when you need to streamline task execution by selecting the most effective tools, as it recommends specific tools based on historical success rates and usage patterns, and provides ranked suggestions that adapt to user feedback and execution data. It solves problems of tool discovery and optimization, and takes in tool capabilities and user feedback as inputs, outputting ranked tool recommendations. Ideal for use in environments where efficient task completion is crucial, such as software development and workflow automation.

Canonical page: https://skillsregistry.net/skills/aegis-ai-cooperative-mcp-toolselect  
JSON: https://api.skillsregistry.net/v1/skills/aegis-ai-cooperative-mcp-toolselect

## Description

An MCP server that recommends specific tools for tasks by learning from usage patterns and historical success rates. It enables users to register tool capabilities and provides ranked recommendations that adapt based on feedback and execution data.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** productivity
- **Updated:** 2026-04-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/x9x0lht789)
- **Repository:** <https://github.com/Aegis-AI-Cooperative/mcp-toolselect>

## 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": "aegis-ai-cooperative-mcp-toolselect"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/aegis-ai-cooperative-mcp-toolselect` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/aegis-ai-cooperative-mcp-toolselect/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