"Understanding Integrated Knowledge Graphs" matching MCP servers:

A zero-dependency Node.js playground for debugging how MCP clients authenticate to an MCP server over HTTP.

Provides a per-person MCP interface to a knowledge graph of legal matters, enforcing OPA-based access barriers and logging every request in a hash-chained audit trail.

Enables agents to perform Schnorr zero-knowledge identification and cryptographic attestation through a native MCP interface, including commitment-challenge-response proofs, JWT validation, Merkle inclusion checks, and replay protection.

Autonomously introspects an undocumented SQLite database to expose auto-generated CRUD tools, join-explaining prompts, and schema resources for LLM agents. All queries run through pre-validated parameterized SQL templates, so the model never writes or sees raw SQL, with full audit logging of every operation.

This MCP server autonomously introspects SQLite databases to auto-generate CRUD tools and join prompts, while enforcing zero-knowledge security through pre-validated SQL templates.

Enables EVTX (Windows Event Log) analysis via Hayabusa, providing tools to scan event logs and retrieve detection rules.

MCP server for Wundervault zero-knowledge secret management. Exposes vault secrets to AI agents via the Model Context Protocol — secrets are decrypted server-side and never returned to the agent in plaintext.

Provides 14 MCP tools for AI agent infrastructure, enabling knowledge base queries, skill search, handoffs, blueprint validation, trust scoring, identity verification, SLA validation, and compliance checks.

Exposes the five Enternovate security tools as 23 Model Context Protocol tools, enabling agents to scan attack surfaces, query knowledge graphs, audit websites, check email security, and run POPIA compliance assessments via a single MCP connection.

Enables AI assistants to fully control a Tracecat SOAR platform instance through natural language, managing workflows, actions, cases, secrets, tables, schedules, graphs, and more.

Enables MCP clients to guard agent API requests against nonce replay attacks using a sliding-window ledger, constant-time digest checks, JWT claim validation, Merkle inclusion proofs, and Schnorr zero-knowledge verification.

Enables AI agents to query cryptographically verified facts with zero-knowledge proofs, selective disclosure, and tamper-evident provenance.

Enables zero-knowledge proof generation and verification, identity verification, and gate checks for privileged agent actions.

Enables secure validation of agent credentials through constant-time digest comparison, JWT HMAC-SHA256 checks, Merkle inclusion proofs, Schnorr zero-knowledge verification, and nonce replay protection. It integrates natively with MCP clients to harden autonomous agent authentication workflows.

A local security knowledge base that indexes documentation like CVEs and CWEs using hybrid keyword and semantic search. It enables LLM agents to query indexed materials via MCP for accurate, offline retrieval during security audits and code reviews.

An MCP server that provides AI agents with real-time package health data, vulnerability reports, and dependency graphs from PyPI and OSV.dev.

Enables agents to construct SHA-256 Merkle trees, generate and verify state inclusion proofs, validate JWT HMAC signatures, perform Schnorr zero-knowledge proofs, and enforce nonce replay protection for immutable state attestation.

Enables governed, audit-traced AI access to a curated knowledge base through the Model Context Protocol, with OAuth 2.1 authentication and policy enforcement for secure, compliant queries.

Exposes standard MCP tools for secure calculation, knowledge-base retrieval, document statistics, and sensitive operations like email, export, and deletion with human-in-the-loop approval.

Enables AI agents to invoke MCP tools only when the call satisfies a private, zero-knowledge proof policy, forwarding authorized calls to upstream servers while keeping policy details private.