"A server for reading, writing, and modifying Rust and C code with Cargo tooling support" matching MCP servers:

An MCP service for AI-assisted reasoning and editing on long-form fiction projects. It builds a structured index from scene files for targeted context retrieval.

A MCP server to allow the LLM in Cursor to access Rust Analyzer, Crate Docs and Cargo Commands.

A Node.js-based MCP server that enables AI agents to generate embeddings, index documents, and perform semantic vector searches using OpenAI and Chroma. It facilitates the creation of retrieval-augmented generation (RAG) pipelines for internal knowledge assistants and document-based workflows.

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.

A multi-tool AI assistant system that uses Model Context Protocol to connect language models with various tools, including math calculations and weather information.

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.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

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

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

Provides a standardized protocol for tool invocation, enabling an AI system to search the web, retrieve information, and provide relevant answers through integration with LangChain, RAG, and Ollama.

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.

Provides structured dealer brand data including inventory, promotions, reviews, and dealer profile via MCP tools, enabling LLMs to answer accurate brand-related queries.

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.

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.

A local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.

Enables semantic search over codebases using natural language queries, returning relevant code snippets with source locations. Integrates with Claude Code for automatic codebase exploration.