"Markdown MCP (Model Context Protocol) Server" matching MCP servers:

IMCP - Insecure Model Context Protocol The DVWA for AI Security! Welcome to IMCP – a deliberately vulnerable framework that exposes 16 critical security weaknesses in AI/ML systems. Whether you're a security researcher, developer, or educator, IMCP is your playground for hands-on learning about real

Implements a secure message communication protocol for handling exchanges between the banking chatbot and Azure OpenAI, providing message queuing, reliability, and detailed logging.

Deterministic dependency + CVE context for AI coding tools, over the Model Context Protocol. A ~0.85 MB pure-Rust MCP server.

Trust, identity, and reputation infrastructure for AI agents. Register agents with W3C DID (Ed25519), check EigenTrust reputation scores, submit peer attestations, search agents by capability, and verify IPFS-anchored audit trails. 11 tools.

Security-enforcing MCP proxy that sits between an AI agent and any number of downstream MCP servers, intercepting every tool call through a capability-token policy gateway that can allow, deny, or escalate to human approval before the call reaches any real tool. It also exposes built-in operator tools for approval workflows, audit trail queries, token management, voice/HUD output, and hierarchical

A Model Context Protocol server that provides tools to manage Keycloak users and realms, allowing you to create and delete users, list available realms, and view users in specific realms.

MCP/REST endpoints for token safety scans, honeypot checks, ecosystem stats, and on-chain task rewards.

An educational project that deliberately implements vulnerable MCP servers to demonstrate various security risks like prompt injection, tool poisoning, and code execution for training security researchers and AI safety professionals.

Provides redacted access to a private local knowledgebase for coding agents, allowing them to inspect files while hiding sensitive names and identifiers.

Local MCP server for Bind Protocol — credential parsing, verification, and hashing tools for AI agents.

A local MCP server that acts as a policy-based firewall for personal context, letting users control agent access to their data with deny-by-default rules, per-field grants, and an audit trail.

A security wrapper for MCP servers that provides trust-on-first-use pinning, guardrail scanning, and protection against prompt injection attacks. It acts as an intermediary layer to ensure universal compatibility and secure enforcement of server configurations across various MCP host applications.

Gives AI agents governed context about a data warehouse — table meaning, ownership, lineage, freshness, and PII flags — plus read-only, row-limited, PII-protected querying across DuckDB, Snowflake, and Databricks. Guardrails enforced at parsing, connection, and result layers keep agents from writing, running away, or leaking personal data.

A production-grade, type-safe MCP server for memory forensics via Volatility 3, enabling LLM-assisted incident response without timeouts or evidence spoliation.

Enables multiple users to share an AI-maintained markdown knowledge base with per-person privacy enforced by the server, so any MCP-capable assistant can recall and save private notes, tasks, and decisions alongside reviewed team and role-gated silos. Access is scoped by identity-provider roles, keeping each person's silo readable only by them while shared knowledge stays available to the whole team.

Autopoietic digital protocol for verifying human-AI authorship. Implements the 51/49 functional convention via SHA-256 hashing and MCP tools (certify_authorship). Ready for Blockchain anchoring.

Enables authenticated MCP clients to query Security Context tools against a git tag or commit ref while returning only vulnerabilities and fix fingerprints that predate that snapshot, so agents do not receive live bugs at the tag.

Enables managing personal information with dynamic topic-based organization (tasks, meetings, contacts, etc.), supporting optional OTP authentication and AES-256 encryption for sensitive data with automatic backups.

MCP server for deterministic context preflight, token counting, and credential redaction for coding agents, with a free local tier up to 12,000 characters and paid HTTP fallback for larger inputs.

Enables AI agents to retrieve only user-approved personal life records through a read-only search tool, with citations and local policy checks on purpose, audience, expiry, and revocation.

Loads signed, verified markdown capsules into AI agents, refusing any capsule without a valid signature from a trusted key. Enables secure, provenance-checked context loading for agents.

Local MCP server for private, consent-based speaker identification and attribution, with per-language voiceprints and calibrated match thresholds. It lets AI assistants know who is speaking in a room or transcript without cloud services.

An MCP server that provides access to Google's Access Context Manager API, enabling management of service perimeters and access levels through natural language.

Official reference MCP server for A202, the Verifiable Agreement Protocol for Agent-Led Commerce. Gives an agent the seven capabilities two organisations need to buy and sell directly: issue a mandate, check what an agent may do under it, approve an act needing a person, form an agreement, exchange obligations, verify a record by replay, and read the transaction record back.

The accountability layer for AI agents — a named human's signed yes before an agent does anything irreversible (payment, record change, deploy), then an offline-verifiable Trust Receipt. Apache-2.0, formally verified.

Indexes a workspace and exposes code-navigation tools to Codex, enabling symbol lookup, reference finding, dependency analysis, and security audit for local codebases.

Provides 110+ tools for identity verification, compliance, and workspace operations through the Model Context Protocol.

An in-memory security MCP server for AI agents and coding copilots that prevents sensitive tool parameters and API keys from leaking into LLM context windows. Isolates execution arguments in local RAM using ephemeral cryptographic commitments and deterministic memory zeroization.

Privacy-first, tamper-evident receipts for MCP tool calls. It hashes and signs arguments/results so you can verify what ran, when, without storing raw payloads.

ModelSafetyMCP is an MCP server for scanning machine learning model artifacts for unsafe serialization, malicious model patterns, risky packaging, URL-based artifact scanning, and directory-level triage.