"Support resources for HTTP-related issues or questions" matching MCP servers:

LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.

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

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.

An HTTP-based Model Context Protocol server for RiotPlan that exposes comprehensive planning tools, resources, and prompts for AI agents. It enables full plan lifecycle management, including ideation, shaping, execution tracking, and retrospective generation.

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

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.

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.

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.

Enables job-application lookup and domain support through MCP, exposing tools such as job lookup by ID over a local HTTP endpoint.

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

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.

A reference implementation for creating an MCP server supporting Streamable HTTP & SSE Transports with OAuth authorization, allowing developers to build OAuth-authorized MCP servers with minimal configuration.

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

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.

An Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.

MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.

A proof of concept MCP server for Apache OFBiz

Enables asking questions and performing semantic searches against an Inkeep knowledge base. Deployable to Vercel with Next.js.

Enables ticket management through a REST API and support document search via a local vector database, powered by Ollama and LanceDB.

Enables searching and accessing Readwise highlights and documents through HTTP endpoints using the Model Context Protocol. Provides vector and full-text search capabilities with streaming responses for retrieving reading highlights and notes.

HAL (HTTP API Layer) is a Model Context Protocol (MCP) server that provides HTTP API capabilities to Large Language Models.

Multi-user MCP gateway for WeKnora v0.7.1 that accepts per-request WeKnora API keys, enabling client-scoped access to spaces and knowledge bases through a single Streamable HTTP MCP endpoint.

A Python server implementing the Model Context Protocol to provide customizable prompt templates, resources, and tools that enhance LLM interactions in the continue.dev environment.

Enables creation and management of knowledge graphs with entities, relationships, and observations through HTTP streaming. Supports persistent storage, search functionality, and CRUD operations for building and querying interconnected knowledge bases.

Enables LLMs to perform sophisticated web searches through proxy servers using Tavily's API, supporting comprehensive web searches, direct question answering, and recent news article retrieval with AI-extracted content.

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.

This MCP server provides a cost-optimized personal-knowledge brain, enabling AI agents to query imported documents via hybrid search and synthesis at minimal monthly spend.