Launchstack
AI-powered StartUp Accelerator Engine built with Next.js, LangChain, PostgreSQL + pgvector. Upload, organize, and chat with documents. Includes predictive missing-document detection, role-based workflows, and page-level insight extraction.
What is Launchstack?
Launchstack is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to ai-powered startup accelerator engine built with next.js, langchain, postgresql + pgvector. upload, organize, and chat with documents. includes predictive missing-document detection, role-based workfl...
AI-powered StartUp Accelerator Engine built with Next.js, LangChain, PostgreSQL + pgvector. Upload, organize, and chat with documents. Includes predictive missing-document detection, role-based workflows, and page-level insight extraction.
This server falls under the Business Applications category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- AI-powered StartUp Accelerator Engine built with Next.js, La
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx launchstackConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Launchstack
LaunchStack is an AI-powered startup accelerator engine built on Next.js, LangChain, PostgreSQL with pgvector, and Neo4j knowledge graphs. It lets you upload and organize business documents, run semantic RAG (retrieval-augmented generation) queries against them, detect predictive missing documents in your startup workflow, and extract page-level insights — all through a chat interface. Teams use it to accelerate due diligence, investor preparation, and knowledge management for early-stage companies.
Prerequisites
- Node.js 18+ and pnpm installed
- PostgreSQL with pgvector extension enabled (or a compatible cloud database)
- OpenAI API key for LLM and embeddings
- Neo4j instance for knowledge graph features (optional but recommended)
- An MCP-compatible client such as Claude Desktop
Clone the repository
Clone the LaunchStack repository from GitHub and navigate into the project directory.
git clone https://github.com/Deodat-Lawson/LaunchStack.git
cd LaunchStackInstall dependencies
Install all project dependencies using pnpm.
pnpm installConfigure environment variables
Create a .env file at the project root and supply your database URL, OpenAI key, and any optional service credentials. The engine reads these at startup to wire its storage, LLM, embedding, and job dispatcher ports.
DATABASE_URL=postgresql://user:password@localhost:5432/launchstack
OPENAI_API_KEY=sk-...
NEO4J_URI=bolt://localhost:7687
NEO4J_USERNAME=neo4j
NEO4J_PASSWORD=your_passwordRun database migrations
Initialize the PostgreSQL schema, including the pgvector extension required for semantic search.
pnpm db:migrateStart the development server
Launch the Next.js application. The MCP server endpoint will be available once the app is running.
pnpm devConfigure your MCP client
Add LaunchStack to your Claude Desktop (or other MCP client) configuration file so the client can connect to the running server.
Launchstack Examples
Client configuration
Add LaunchStack to your claude_desktop_config.json. The server must already be running locally.
{
"mcpServers": {
"launchstack": {
"command": "npx",
"args": ["launchstack"],
"env": {
"DATABASE_URL": "postgresql://user:password@localhost:5432/launchstack",
"OPENAI_API_KEY": "sk-..."
}
}
}
}Prompts to try
Example prompts for interacting with uploaded startup documents through LaunchStack.
- "Summarize the key financial projections from the uploaded pitch deck"
- "What documents are missing from a standard Series A due diligence checklist?"
- "Extract all mentions of market size from the business plan and compare them"
- "What risks are identified across all uploaded investor materials?"Troubleshooting Launchstack
pgvector extension not found when running migrations
Connect to your PostgreSQL database and run 'CREATE EXTENSION IF NOT EXISTS vector;' as a superuser before running migrations.
OpenAI embedding calls fail during document ingestion
Verify that OPENAI_API_KEY is correctly set in your .env file and that your OpenAI account has access to the text-embedding-3-small model.
Knowledge graph features return empty results
Ensure your Neo4j instance is running and that NEO4J_URI, NEO4J_USERNAME, and NEO4J_PASSWORD are correctly configured. Test the connection with the Neo4j Browser before ingesting documents.
Frequently Asked Questions about Launchstack
What is Launchstack?
Launchstack is a Model Context Protocol (MCP) server that ai-powered startup accelerator engine built with next.js, langchain, postgresql + pgvector. upload, organize, and chat with documents. includes predictive missing-document detection, role-based workflows, and page-level insight extraction. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Launchstack?
Follow the installation instructions on the Launchstack GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Launchstack?
Launchstack works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Launchstack free to use?
Yes, Launchstack is open source and available under the Apache-2.0 license. You can use it freely in both personal and commercial projects.
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