"Elastic Stack" matching MCP servers:

Connects to Stack AI workflows, allowing you to run workflows and pass user inputs through MCP-compatible clients.

Refines and improves AI prompts using workspace-aware context from your project's tech stack, structure, and dependencies. Includes tools to analyze prompt quality and generate well-structured prompts from raw ideas.

Enables making REST API calls to Teradata cloud services including Elastic Compute, Vector Store, OMS, and QueryGrid. Supports custom authentication, Socks5 proxy, and multipart file uploads.

An MCP server that enables analyzing and querying GitHub repositories through the GitHub Chat API, allowing users to index repositories and ask questions about their code, architecture and tech stack.

Connects to Elasticsearch clusters through the Model Context Protocol, enabling natural language querying and management of Elasticsearch data. Provides tools to search indices, list available indices, and retrieve index mappings.

Enables interaction with Aiven cloud services including PostgreSQL, Kafka, ClickHouse, Valkey, and OpenSearch. Allows LLMs to list projects, services, and retrieve service details to build full-stack solutions across the Aiven ecosystem.

An advanced contextual memory server for agent orchestration providing chronological history, semantic vector search via Redis Stack, and temporary scratchpad storage. It also enables context compression through history rollups and facilitates inter-agent communication using a Redis-based Pub/Sub system.

Searches real developer solutions from Stack Overflow, Reddit, GitHub issues, and forums to find battle-tested fixes and workarounds for specific programming problems. Bypasses AI guessing by finding actual community discussions where developers have already solved your exact issue.

Turns any URL into structured web intelligence in one call: SEO/OpenGraph metadata, public contacts, tech-stack fingerprinting, Schema.org data, a security-headers audit, and clean AI-ready Markdown. Anti-SSRF hardened by design.

An Elasticsearch-based AI memory system optimized for Chinese that enables persistent knowledge storage and complex entity relationship management via the Model Context Protocol. It features advanced semantic search using the IK analyzer and supports multi-zone memory isolation for specialized knowledge graphs.

A full-stack SMS assistant that integrates MessageMedia SMS API with OpenAI's GPT models, enabling AI-driven SMS conversations and message management through function calling and contextual memory.

Minimal local RAG stack with an MCP server that provides document search for any agent.

Provides a local groundedness verifier as an MCP server, returning a verdict on whether a draft answer is supported by provided document excerpts.

A fully local AI stack that provides OpenAI/Anthropic-compatible LLM API, embeddings, mem0 memory, and second-brain RAG via MCP tools, all running independently with no cloud dependencies.

Enables users to connect and run Stack AI workflows directly through MCP-compatible clients. It allows for passing user inputs to specific projects and receiving structured responses from deployed AI applications.

A local-embeddings RAG + Model Context Protocol server that provides retrieval-backed knowledge of the Wawona stack to Cursor models.

Provides AI agents with a comprehensive web intelligence stack including crawling, private search via SearXNG, and intelligent RAG capabilities for focused content extraction. It supports advanced features like semantic vector search and knowledge graph integration for code validation to enhance AI performance and reliability.

Connects AI assistants to Exa AI's search capabilities, including specialized code search across GitHub repos, documentation, and Stack Overflow, plus web search, company research, and deep research tools for comprehensive information retrieval.

Connects AI assistants to Exa AI's search capabilities, enabling web search, company research, URL crawling, LinkedIn search, and specialized code search across GitHub repos, documentation, and Stack Overflow for finding relevant coding context and examples.

Enables verification of portfolio claims by resolving citations to exact supporting sentences at build time, providing read-only tools to list work, find evidence, check stack mentions, and read case studies while failing the build on any unverifiable claim.