"Setting up an MCP server in Kubernetes" matching MCP servers:

Enables Codex to rank available tools and skills, rerank code and documentation search results, and triage saved output artifacts using Jev-based relevance scoring while leaving final decisions to Codex.

All In One Model Context Protocol: qdrant, google suite (gmail, calendar, ...), jira, gitlab, CLI, ...

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Enables agents to optimize context-window attention by reordering retrieved documents so critical evidence lands at prompt boundaries, mitigating lost-in-the-middle degradation. It combines BM25 lexical scoring, dense vector similarity, reciprocal rank fusion, knowledge-graph expansion, and recency-decay memory caching, exposed as a zero-dependency MCP stdio server.

Enables agents to run hybrid retrieval, reciprocal rank fusion, knowledge graph expansion, semantic caching, and context reordering so critical evidence is placed at prompt boundaries to reduce lost-in-the-middle degradation.

Enables MCP clients to query a document knowledge base with permission-aware hybrid retrieval, listing sources, searching snippets, and fetching document context while reporting confidence for each result.

Enables AI coding agents to retain and recall project context across sessions through local Markdown storage and hybrid keyword/semantic retrieval, including reusable knowledge cards. It runs offline as a daemon and integrates with MCP-compatible IDEs to continue long-running work without re-explaining decisions or architecture.

A Node In Layers package that simplifies creation of MCP (Model-Control-Protocol) servers with tools for defining models, adding CRUD operations, and interacting with clients.

Enables integration with financial transaction data through REST APIs, PostgreSQL databases, and document storage systems. Demonstrates agentic AI capabilities by connecting to Alpha Vantage API and managing financial data through natural language interactions.

Context Mode is an MCP server that reduces context window waste by sandboxing data-heavy tools, tracking session state in SQLite, and promoting code-based analysis over raw data reads, achieving up to 98% context savings.

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

A version-aware Kubernetes documentation assistant that connects LLMs to trusted, real-time Kubernetes docs to reduce hallucinations and ensure accurate, version-specific responses.

AI-powered MCP server for enterprise OpenShift/Kubernetes cluster management, providing diagnostic tools, RAG knowledge retrieval, and autonomous remediation recommendations.

Exposes search, locate, expand, and find_related tools over MCP so AI coding agents in Claude Code, Cursor, Copilot, and other clients can retrieve the best code chunks (path, lines, snippet) by meaning instead of grep or glob. This hybrid code search lets agents find the right files in fewer steps, using up to 50% fewer tokens.

Converts PDF, Word, PowerPoint, Excel, and HTML documents into Markdown, handling files up to 8 MB in a single call and routing larger or scanned files through an OCR and table-detection queue that returns Markdown plus a JSON structure file. Results arrive either by polling or a signed webhook.

Enables AI agents to query up-to-date, sourced information about workflow automation services, AI agents, integrations, pricing, case studies, FAQs, and contact details in Dutch and English through read-only tools.

Enables running durable, traceable AI agents via LangGraph through a universal MCP interface, integrating with Hatchet for orchestration, logging, and retries. Provides tools for knowledge management (ingestion, RAG) and Kubernetes operations (diagnosis, auto-fix).

Web search for AI agents. Up to 10 results for $0.001 USDC via x402 on Base. No API key.

Enables natural language management of Hammerspace storage clusters with automated file ingestion, tagging, tier management, and vector embedding generation. Supports real-time file monitoring, multi-format document processing, and Kubernetes-based ingestion workflows with Milvus integration.

WordPress plugin that runs an MCP server on your own site: search and read published posts and pages, look up WooCommerce products, describe the site as schema.org types and query site figures, with drafts only when the site enables them. Signed-in access by default; anonymous access and OAuth are optional and off.

Provides up-to-date documentation for AI agents by locally querying a community-driven registry of pre-built docs packages.

Context9 is an MCP server that feeds AI agents with up-to-date documentation, reducing hallucinations by real-time knowledge synchronization.

Enables AI agents to securely retrieve pre-compiled bounded context and memory state over a zero-network Unix Domain Socket, ensuring tenant isolation and sub-millisecond rehydration in Kubernetes environments.

An MCP server that gives AI coding assistants access to up-to-date API documentation via RAG by crawling documentation sites, indexing them into a vector store, and enabling semantic queries.

An MCP server that retrieves relevant code snippets and documents to assist in generating pymilvus code, converting between ORM and client, and translating Milvus code between programming languages.

An archived, unsafe MCP server with critical security vulnerabilities, classified as a pump and dump operation. Do not use in production.

An MCP server that provides full-text search over documentation using Whoosh, enabling AI assistants to find up-to-date, authoritative answers.

Enables intelligent Kubernetes deployments, automated documentation testing, organizational pattern management, and shared prompt libraries. Provides AI-powered recommendations based on cluster capabilities and automates DevOps workflows through conversational interfaces.

An MCP server that enables AI assistants to access up-to-date documentation for Python libraries like LangChain, LlamaIndex, and OpenAI through dynamic fetching from official sources.

An MCP server providing semantic search over ESP32 documentation, including ESP-IDF guides, API references, and Technical Reference Manuals, enabling coding agents to look up ESP32 facts locally with accurate, chip-specific results.