Alternatives
Products that do what Morphik – Open-source MCP server for technical document search does
Hey HN - we built Morphik MCP to solve a common problem: finding specific information across scattered technical docs. We've experimented with GraphRAG, ColPali, contextual embeddings, and more. MCP emerged as the solution that unifies these approaches. Features: - Multimodal search across text, diagrams, and videos - Natural language knowledge base management - Fully open-source with responsive support What sets MCP apart is its ability to return images (including diagrams) directly to the MCP client. Users have applied it to search over data ranging from blood tests to patents, and we use…
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Hey, I'm Nick from Nutrient, I want to share our newly released MCP Server that enables document workflows using natural language — things like redacting, merging, signing, converting formats, or extracting data. While many MCP servers have traditionally been developer-focused, we recognized that the technology could be highly effective in promoting the adoption of tools that are often hidden from end-user interfaces. We’re really interested to see if this side of the protocol could continue to mature. One thing we struggled with was the inability to receive documents from the client (no…
2025 · github.com
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An OKF-backed Model Context Protocol (MCP) server delivering persistent long-term memory and SQLite FTS5 search for AI agents. - fellowgeek/mcp-memory
24d ago · github.com
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Jul 2026 · github.com
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After getting frustrated with macOS's Spotlight search, e.g., typing "driver license" doesn't give me anything unless the file name matches exactly, I thought, why not index my entire Documents folder? This way, I can find that one PDF or image buried deep in subfolders using natural language queries. So I built SmartSearch; it uses SentenceTransformers for embeddings and FAISS for fast similarity search. Best of all, it runs locally on your computer. Github: https://github.com/neberej/smart-search/ Demo:…
2025 · github.com
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2018 · typesense.org
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Code Index MCP is an MCP server that indexes codebases and provides search capabilities to LLMs. Supports 50+ file types with automatic indexing, regex/fuzzy search, code analysis, and real-time file monitoring. LLMs can search your entire project, find files with glob patterns, analyze code structure (functions, classes, imports), and get automatic updates when files change. Eliminates the need to manually copy files or explain project structure to overcome context limits. Built with Python using the Model Context Protocol. Uses pluggable search backends…
2025 · github.com
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Hi HN, I built XRAY MCP after discovering that AI assistants were scanning my projects with plain grep and guessing. I tried direct tree-sitter integration and language servers; both felt heavy for a lightweight tool. ast-grep hit a sweet spot: syntax-aware search in a single binary. XRAY MCP wraps it behind three endpoints—map, find, impact—so a model (or human) can answer questions like “what breaks if I change this function?” on demand. It’s stateless, supports Python/JS/TS/Go, and installs quickly. Repo: https://github.com/srijanshukla18/xray Would love…
2025 · github.com
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I built this because I got tired of watching Claude Code read through massive files just to find a few functions. Sourcerer lets AI agents search code semantically and grab exactly the code chunks they need instead of burning tokens on whole files. It uses tree-sitter to parse your codebase and creates a searchable index. So instead of "read auth.py (538 lines)", an agent can search for "user authentication logic" and get back just the relevant functions. Demo: https://asciinema.org/a/736638 GitHub: https://github.com/st3v3nmw/sourcerer-mcp
2025 · github.com
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Hi HN! I built Docuglean, an open-source SDK for intelligent document processing that works with OpenAI, Mistral, Google Gemini, and Hugging Face models. The idea came from repeatedly writing boilerplate code to extract structured data from invoices, receipts, and other documents. Instead of wrestling with different API formats, I wanted a unified interface that: - Extracts structured data using Zod/Pydantic schemas - Classifies and splits multi-section documents (e.g., medical records) - Processes documents in batches with automatic error handling - Works locally without APIs (for…
Nov 2025 · github.com
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Dear HN Community, I am a long time fan and first-time contributor. I just launched a developer focused semantic search platform and wanted to share it with the community. The idea is simple: upload structured or unstructured documents, select the fields you want to index and tag as metadata, and instantly get a clean search API you can use in your own app. Here is what it currently supports: - Manage your own tenants and projects - Upload .json and .txt files (support for .pdf, .docx, .xlsx, .yml, etc. coming soon) - Expose 3 APIs: search, upload document (embeddings), and delete document -…
2025 · aisearch.vpuna.com
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2025 · github.com
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MCP (Model Context Protocol) server that lets AI assistants check domain availability in real-time. Features: - Multi-source: Porkbun, Namecheap, RDAP, WHOIS - Price comparison across registrars - Social handle checking (GitHub, Twitter, npm, etc.) - Premium domain detection with pricing insights Works with any MCP-compatible client. Install: npx -y domain-search-mcp
Dec 2025 · github.com
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Hi HN — I'm the creator of FastMCP and wanted to share a new project we've open-sourced called Colin. I obviously love MCP, but I also use skills extremely heavily in my day-to-day work. Being exposed to both has made me very aware of a tension: - Anything with dynamic information, I ship over MCP. This takes work to set up and requires conversational boilerplate to refresh in every conversation. - Anything behavioral, I put in skills. They're lightweight, used automatically, and feel great. But I would never put dynamic information in a skill because keeping it up to date is a pain. And yet…
Jan 2026 · github.com
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How it works: - Storage uses one SQLite database file, plus a local LanceDB index of vectors. No need for a server, cloud services, or any API keys. - Retrieval is a hybrid approach using BM25 (rank-bm25) and vector-based search (sentence-transformers) combined with a co-occurrence graph of entities, using reciprocal rank fusion. The idea is to find the right memory, not the closest one. - It plugs into the agent's lifecycle via MCP: before the agent responds, relevant memories are added to its input; after each turn, decisions and new learnings are automatically recorded. No need to…
Jun 2026 · github.com
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Hello HN, I built this because I wanted to give Claude Desktop access to my Notion workspace without running a flaky local Python script via stdio. This is a Node.js/Express implementation of the Model Context Protocol (MCP) that uses SSE (Server-Sent Events) for transport. It’s designed to be stateless and deployable as a container (I'm hosting it on Apify, but it works anywhere with Node). The Stack: TypeScript + Express @modelcontextprotocol/sdk Zod for input validation Bearer Auth for security (since it exposes an HTTP endpoint) Capabilities: It allows the LLM to search pages,…
Dec 2025 · github.com
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Open-source & web based MCP client. Chat with any MCP server in your own app. Powered by CopilotKit & Composio. Shipped this with cursor over the weekend and built: 1. The first web-based MCP client (deployed version on GH) 2. An open-source client you can add into any app. Built using CopilotKit for the client and interactivity layer + agent frontend which connects to a LangGraph ReAct agent that coordinates MCP calls. Uses Composio's MCP server.
2025 · github.com
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I’ve been building Canine for about 2 years now, and have slowly grown it to about ~1000 developers using it for deploying all sorts of apps / projects / etc. Amazingly, the whole thing is still able to run on a single 48GB Hetzner VPS. Think of it basically like Coolify, for Kubernetes. I previously posted about it here: https://news.ycombinator.com/item?id=44292103 Recently, we added MCP capabilities to canine, and I was shocked how well it worked. It basically is able to create services, cron jobs, databases, get the logs for these and redeploy. See it here:…
Apr 2026
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Stop your coding agent from guessing at datasheets
Jun 2026 · docs.byteask.ai
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I built https://ask.rivestack.io — a semantic search engine over Hacker News posts. Instead of keyword matching, it finds results by meaning, so you can search things like "best way to handle authentication in microservices" and get relevant threads even if they don't contain those exact words. How it works: Indexed HN posts and comments into PostgreSQL with pgvector (HNSW index) Embeddings generated with OpenAI's embedding model Queries run as nearest-neighbor vector searches — typical response under 50ms The whole thing runs on a single Postgres instance, no separate vector DB I…
Feb 2026 · ask.rivestack.io
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