"How to Test Kubernetes Network Policies" matching MCP servers:

Enables Claude Code to interact with network devices over serial and SSH with command safety classification and a persistent knowledge base.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Public browse-first MCP server for AI capability discovery and grounded Agent feedback. The knowledge graph is read-only and ordinary visits do not trigger search or automatic posting.

Turn Obsidian notes into agent-ready context, preview-only plans, and safe repo handoffs.

The shared route network for AI agents. Query verified step sequences plus documented failure modes ("routes") for API tasks over MCP, contributed and attested by agents. Reads are free and keyless. Semantic retrieval with a confidence-refusal threshold and per-route verification tags. 9,700+ routes across 2,100+ domains. A service of MC Software, LLC.

Enables AI agents to interact with the AI Network blockchain by managing accounts, submitting transactions, and reading database values. It supports registering Hyper Agents and accessing a Layer 2 DAG-based shared agent memory system based on staking status.

Enables AI agents to interact with the Coherence Network platform, allowing them to browse ideas, record contributions, and access governance features via natural language.

Enables querying and managing personal/team internal knowledge from sources like Slack, Gmail, and Drive through semantic search and retrieval.

MCP server that connects AI agents to Google NotebookLM, enabling natural language interaction with notebooks, including Q&A, source ingestion, and audio overview generation.

Enables semantic search and retrieval of personal and team knowledge from connected sources like Slack, Gmail, Google Drive, and Dropbox, with the ability to save new information for future recall.

Enables local-first knowledge management for Codex, providing tools for guided discussions, contextual recall, review, and daily topics.

Builds a searchable memory bank from persona-specific PDF content and exposes it as an MCP tool for querying.

Enables building and querying knowledge graphs by ingesting documents into Neo4j using Gemini for entity extraction, and exposes MCP tools for graph health, document ingestion, and knowledge base querying.

A local Retrieval-Augmented Generation system that enables users to ingest markdown files into a FAISS-powered vector knowledge base for semantic search. It provides tools for document indexing and context retrieval to support informed LLM queries without external dependencies.

Self-improving, verifiable memory for AI coding agents. Learns how you work, stops repeating mistakes, models each project, recalls the right lesson at the right moment. Every memory is signed and tamper-evident. Local-first.

Semantic memory for AI builders: capture the tacit engineering know-how that never reaches your docs, recall it the moment it applies. Built in Rust on Postgres and pgvector.

Connects AI agents to persistent topological memory on the Volumetric Lattice Network, enabling sub-5ms associative recall and storage of facts, documents, and code.

Enables AI assistants to perform over 80 Obsidian vault operations locally via the Obsidian CLI, with a single tool and no network dependencies.

Campaign orchestration MCP server for AI agents — dependency DAGs, parallel fan-out, failure policies, and embedded notes.

A read-only MCP server providing tools to search and retrieve insurance product information, coverage details, and compare policies from a pre-built knowledge graph of Belgian insurance products, with verbatim citations from source PDFs.