"A tool for analyzing user feedback data to support app product development" matching MCP servers:

Enables an ElevenLabs support agent to call support tools over MCP, including Discord ticket flows, post-call webhook handling, and knowledge-base syncing.

A custom MCP tool that integrates Perplexity AI's API with Claude Desktop, allowing Claude to perform web-based research and provide answers with citations.

Exposes order status lookup and knowledge base search tools from the Support Agent AI over MCP, enabling MCP clients to handle customer support queries with grounded, citation-backed answers.

A full-feature MCP server that serves as a product-development copilot, providing RAG search, SQL queries, and inline chart visualizations from seeded product data, with per-user identity and its own OAuth login.

Enables AI assistants to handle customer support by looking up order status, semantically searching knowledge bases, and creating support tickets through MCP tools, with grounded answers and automated evaluations.

Enables a support bot to answer FAQ questions from a local vector store, with admin tools to add, list, and delete knowledge entries while enforcing read-only versus admin bearer-token permissions.

Enables support engineers to analyze tickets against a help center with cited retrieval, role-gated and human-confirmed actions, and safety-gated evaluation.

Enables local data discovery by indexing metadata from SQLite, CSV, and Markdown sources, providing hybrid keyword and TF-IDF semantic search via MCP tools (listSources, indexSource, search, getSchema) and a REST API.

Enables natural language querying and semantic search over a bilingual customer support ticket dataset using SQL and embeddings.

A basic MCP server setup guide demonstrating how to configure and run Python-based MCP servers with integration examples for Bright Data web scraping and Apify Actors for product data collection.

A local stdio MCP server that brings scattered tickets, transactions, and current policies together so a model can retrieve evidence, assess cases, and prepare reply and escalation drafts. All writes stay local and pending human review, with no ability to send messages, move money, change accounts, or publish content.

Enables agents to send only the handful of tool definitions relevant to each question, ranking a large catalog by keywords and optional embeddings to cut context cost and wrong-tool picks. It can also run in front of any mcpServers config as a proxy that exposes just search_tools and call_tool instead of the whole catalog.

Exposes a support-ticket inbox as tools an AI client can use to list, inspect, triage, and update tickets, including LLM-based category, priority, and sentiment classification with a drafted first response informed by similar past tickets. It works with a mocked dataset styled after a home-loan partner-support inbox, with the tool interface designed so a real ticket source could be swapped in later.

A universal MCP tool gateway that manages multiple remote tool processes, enabling LLMs to dynamically invoke web scraping, summarization, and knowledge retrieval through standardized Function Calling.

Enables AI agents to check order statuses, retrieve FAQ policy answers via RAG, and create/manage support tickets, all based on the e-commerce support workflow in the repository.

Enables enterprise SaaS support teams to get retrieval-augmented answers from indexed support documentation and to run natural-language questions as SQL queries against a support PostgreSQL database. It returns answers with source references and exposes the generated SQL alongside its results, with optional tracing and evaluation.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

An MCP proxy that embeds tool definitions and returns only the top-k semantically relevant tools per query, reducing context usage and routing calls to upstream MCP servers.

Provides e-commerce customer support tools for order status, delivery, account, and policy questions, with RAG-grounded retrieval and strict authorization checks over mock data.

Graph-based tool retrieval for LLM agents. Builds a tool graph from OpenAPI/MCP specs and retrieves multi-step workflows via hybrid search (BM25 + graph traversal + embedding), recovering accuracy from 12% to 82% with 79% fewer tokens. Also works as an MCP Proxy to aggregate multiple servers behind 3 meta-tools.

A Model Context Protocol server that provides Claude with a dedicated space for structured thinking during complex problem-solving tasks, helping improve its reasoning capabilities.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

A tool that creates MCP (Model Context Protocol) servers from OpenAPI/Swagger specifications, enabling AI assistants to interact with your APIs.

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

A Model Context Protocol (MCP) server that provides AI-powered customer support using Cursor AI and Glama.ai integration.

Enables AI agents to query structured data refined from unstructured web sources, including developer breaking changes, B2B pricing matrices, regulatory compliance, semantic search, and on-demand URL refinement.

Provides semantic search and knowledge base management for the micro-app micro-frontend framework by ingesting its source code and documentation.

Enables MCP clients to ask bilingual data questions, inspect database tables and schemas, and execute validated read-only SQL through exposed tools.

Enables agents to search across the pooled tools of many connected MCP servers and invoke them through a single endpoint, returning only the handful of tools relevant to each request. Filters by the caller's permissions before ranking, so agents never see or plan around tools their user is not allowed to use.

Enables MCP clients to list, create, and update support tickets, classify them by category, priority, and sentiment, detect duplicates, and answer queue questions using retrieval-augmented LLM tools.