# policymesh

> policymesh — deepakmeena61-policymesh. Use this tool when you need to securely query and manage governed data through natural language, enforcing role-based access control and data protection. It solves problems related to data security, access control, and compliance, providing a governed agentic data API with SQL validation, PII masking, and audit logging. With inputs including natural language queries and outputs of governed data, use PolicyMesh in contexts where sensitive data requires secure and controlled access.

Canonical page: https://skillsregistry.net/skills/deepakmeena61-policymesh  
JSON: https://api.skillsregistry.net/v1/skills/deepakmeena61-policymesh

## Description

PolicyMesh is a governed agentic data API that enforces SQL validation, role-based access control, PII masking, and audit logging at the MCP tool boundary, letting users query governed data through natural language with three MCP tools: query_sql, search_docs (pgvector semantic search), and lookup_metadata (role-filtered schema discovery).

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/iw8izhyjgz)
- **Repository:** <https://github.com/deepakmeena61/policymesh>

## 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": "deepakmeena61-policymesh"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/deepakmeena61-policymesh` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/deepakmeena61-policymesh/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