SMMS_Semantic-Map-MCP-Server
The repository SMMS creates an MCP server for instance-level semantic maps and provides a series of functional modules for 3D instance objects in semantic maps.
Directory
The repository SMMS creates an MCP server for instance-level semantic maps and provides a series of functional modules for 3D instance objects in semantic maps.
Forge is Voxell's hosted text-embedding API. This MCP server exposes two tools — embed (turn text into vectors) and list_models — so any MCP-compatible agent…
Find your files with natural language and ask questions.
AI-Ready Data & Context Engineering API. Connect any data source — PostgreSQL, CRMs, APIs — and get clean, structured, AI-ready data in seconds. Natural…
FinanceGenius.AI is India's first AI-native financial product MCP server. 15 read-only tools that any MCP-compatible AI client (Claude Desktop, Cursor…
Gres is a minimalist AI command server for agents and developers. Snap pages, grab sites, source docs, and ask anything. One interface, zero fluff.
Make any website queryable by AI agents — index any site, ask questions, get cited answers via RAG
Extract clean markdown from any URL. Strips nav/ads/scripts, returns structured content. Built for RAG pipelines and AI research agents. -- x402 micropayment…
Personal YouTube AI knowledge base powered by RAG. Query your subscribed channels.
A MCP Sever demo to explain how to chat with deepseek and how to use MCP tool calling.
A managed Retrieval-Augmented Generation (RAG) server using MCP, integrated with knowledge bases and OpenSearch.
Sifter extracts structured, typed records from your documents (PDFs, scans, contracts, invoices) using a natural-language field spec, then lets an agent query…
This is our final project , in this we have utlized langgraph coupled with various mcp server mounted of fastapi using fastmcp to create mutlifaceted…
Enables Claude to search and retrieve relevant documentation through Inkeep's RAG API, returning structured citation data for technical support and…
Enables AI systems to access and retrieve information from multiple vector store backends including HNSWLib and Weaviate, providing a unified interface for…
A Retrieval-Augmented Generation (RAG) server for document processing, vector storage, and intelligent Q&A, powered by the Model Context Protocol.
A server for Retrieval Augmented Generation (RAG), providing AI clients access to a private knowledge base built from user documents.
A lightweight Python server for Retrieval-Augmented Generation (RAG) using AWS Lambda. It retrieves knowledge from external data sources like arXiv and PubMed.
A RAG-based Q&A server using a vector store built from Gemini CLI documentation.
Transform 17 source types (docs, GitHub repos, PDFs, videos, Jupyter, Confluence, Notion, Slack/Discord) into AI-ready skills and RAG knowledge. 35 MCP tools…
Agentic RAG over your own documents on an embedded LanceDB, no database server to run. Hybrid search with reranking, Docling parsing for PDFs and 40+ formats…
Integrate web crawling and Retrieval-Augmented Generation (RAG) into AI agents and coding assistants.
Privacy-first local RAG server for semantic document search without external APIs
A healthcare-focused RAG server using Groq API and Chroma for information retrieval from patient records.