# courtmesh-mcp

> courtmesh-mcp — thinkscoop-technologies-courtmesh-mcp. Use this tool when you need to search and analyze Indian court case law, as it provides access to over 310 million case records from various courts and tribunals. The courtmesh-mcp server enables AI clients to retrieve relevant case information through the CourtMesh public API, solving use cases such as legal research and case analysis. It accepts search queries as input and returns relevant case data as output, making it ideal for applications requiring Indian court case law insights.

Canonical page: https://skillsregistry.net/skills/thinkscoop-technologies-courtmesh-mcp  
JSON: https://api.skillsregistry.net/v1/skills/thinkscoop-technologies-courtmesh-mcp

## Description

An MCP server for the CourtMesh public API that enables AI clients to search and analyze Indian court case law, covering over 310 million case records from the Supreme Court, High Courts, District Courts, and tribunals.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/mlbbq6vcj7)
- **Repository:** <https://github.com/thinkscoop-technologies/courtmesh-mcp>

## 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": "thinkscoop-technologies-courtmesh-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/thinkscoop-technologies-courtmesh-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/thinkscoop-technologies-courtmesh-mcp/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