home / mcp / attestix mcp server
Provides an attestation infrastructure for AI agents, enabling verifiable identities, credentials, compliance, and provenance with cryptographic proofs.
Configuration
View docs{
"mcpServers": {
"vibetensor-attestix": {
"command": "python",
"args": [
"/path/to/attestix/main.py"
]
}
}
}Attestix is an attestation infrastructure that enables cryptographically verifiable proofs for AI agents, covering agent identities, credentials, delegation, compliance with the EU AI Act, provenance, and blockchain anchoring. It is designed to produce machine-readable proofs that can be presented to regulators, other agents, or systems, while operating offline for core functions and using Ed25519-based signatures and hash-chained audit trails to ensure tamper-resistance and verifiability.
You run the Attestix MCP server as a local process and connect to it from your MCP client or automation scripts. Your client can request identity creation, issue credentials, generate verifiable presentations for regulators, and query or update compliance, reputation, and provenance records. All artifacts are cryptographically signed and verifiable, enabling trust between autonomous agents and external systems.
Prerequisites: you need Python installed on your system. Ensure you have pip available for installing dependencies.
Step 1: Install the Attestix package from Python's package index.
Step 2: If you want to run from source, clone the repository, install dependencies, and start the server.
Step 3: Start the MCP server using the provided runtime command line.
The server exposes a set of tools and services you can invoke through MCP clients. Core security features include Ed25519-based signatures for all artifacts, a hash-chained audit trail, SSRF protection, and optional encrypted key storage when a password is provided. No external API calls are required for core operations.
Security is built into every artifact: identities, credentials, and compliance records are digitally signed with Ed25519, and the audit log uses a SHA-256 chain to ensure integrity. Access control and privacy considerations are enforced for sensitive data, and GDPR-related erasure is supported for identity data when applicable.
Create a Unified Agent Identity Token (UAIT) from any identity source.
Auto-detect token type and register the identity pipeline.
Check existence, revocation, expiry, and signature on an identity.
Convert an identity to A2A, DID Document, OAuth, or a summary.
List UAITs with protocol and revocation filters.
Retrieve full UAIT details.
Mark a UAIT as revoked.
Erase agent data across all stores per GDPR Article 17.
Parse an A2A Agent Card JSON.
Generate agent.json for hosting.
Fetch /.well-known/agent.json from a URL.
Generate ephemeral did:key with Ed25519 keypair.
Generate did:web DID Document for self-hosting.
Resolve any DID to its DID Document.
Create a UCAN-style capability delegation token.
Verify JWT signature, expiry, and structure.
List delegations by agent and role.
Revoke a delegation token.
Record an interaction and update trust score.
Retrieve reputation score with category breakdown.
Search agents by reputation criteria.
Create EU AI Act profile with risk categorization.
Retrieve a full compliance profile.
Update an existing compliance profile.
Perform gap analysis between completed and missing requirements.
Record self or third-party conformity assessment (Article 43).
Generate Annex V declaration and issue a VC.
Filter profiles by risk category and compliance status.
Issue a W3C VC with Ed25519Signature2020 proof.
Check VC signature, expiry, and revocation.
Verify a VC JSON from an external source.
Revoke a Verifiable Credential.
Get full details of a VC.
Filter credentials by agent, type, and validity.
Bundle VCs into a signed VP for a verifier.
Verify a VP with embedded credentials.
Record training data source (Article 10).
Record model chain and metrics (Article 11).
Log an agent action with a hash-chained audit trail (Article 12).
Retrieve full provenance record.
Query audit log with filters.
Anchor identity hash to Base L2 via EAS.
Anchor credential hash to Base L2 via EAS.
Merkle batch anchor of audit log entries.
Verify an on-chain anchor against local data.
Get anchoring status for an artifact.
Estimate gas cost for anchoring.