TrueRAG Compliance Policies
This Model Context Protocol server, developed for integrating with a GraphQL API for policy queries, provides AI assistants with access to state-specific policy information. Built using Python with FastMCP, GQL, and AIOHTTPTransport, it offers tools for connecting to the GraphQL endpoint, generating queries based on user descriptions, and executing those queries. The server implements environment-based configuration for API key management and includes features like schema fetching and query generation assistance. By abstracting the complexities of GraphQL interactions into a standardized MCP interface, it enables AI systems to easily access and analyze policy data across different states. This implementation is particularly valuable for applications requiring up-to-date policy information, facilitating use cases such as legal compliance checks, policy analysis, and state-specific regulatory guidance.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-02.
Scan details: Circle-IR · 2026-09-02 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- ai-ml
- Source
- PulseMCP
- Repository
- github.com/ad-veritas/mcp-server-truerag
- Author type
- human
- Last scanned
- 2026-09-02
- Updated
- 2026-09-02
Use via MCP
Resolve TrueRAG Compliance Policies from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.