# Pleasanter MCP Server

> Use this tool when you need to integrate AI-powered interactions with project management systems, enabling efficient issue management and team productivity insights through natural language. It solves problems of manual data entry, complex search queries, and limited analytics capabilities in project management workflows. The tool accepts natural language inputs and outputs relevant project data, analytics, and insights, making it ideal for use cases where seamless human-AI collaboration is required.

Canonical page: https://skillsregistry.net/skills/takashi-matsumura-pleasanter-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/takashi-matsumura-pleasanter-mcp-server

## Description

Enables AI assistants to interact with Implem.Pleasanter project management systems, supporting issue management, advanced search, analytics, bulk operations, and team productivity insights through natural language.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/f3g2gjha1f)
- **Repository:** <https://github.com/Takashi-Matsumura/pleasanter-mcp-server>

## 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": "takashi-matsumura-pleasanter-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/takashi-matsumura-pleasanter-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/takashi-matsumura-pleasanter-mcp-server/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