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Grapevine

Grapevine

An open-source, self-hostable knowledge hub that unifies your company's tools and gives AI assistants semantic search via MCP.

What is Grapevine?

Grapevine is an open-source, self-hostable unified knowledge store designed to ingest information from a company's scattered tools and turn it into one searchable index. It connects to popular services like Slack, Notion, Linear, GitHub, Google Drive, HubSpot, Salesforce, and more, then uses AI embeddings to enable semantic search across all of them. The platform is built around an MCP (Model Context Protocol) server, which lets AI assistants such as Claude query and retrieve company knowledge directly. Beyond search, Grapevine provides an optional Slack bot for AI-powered question answering and a web-based admin UI for configuring data sources and onboarding organizations. Its architecture includes core services like an ingest gatekeeper, tenant steward, and background workers that process webhook data, generate embeddings, and maintain search indices. This makes it a practical choice for teams that want a private, self-hosted knowledge layer rather than relying on a closed SaaS product. Because Grapevine is self-hostable via Docker Compose or Kubernetes, it appeals to developers and enterprises that need control over their data and infrastructure. It supports a wide range of connectors across communication, project management, documentation, code, CRM, design, analytics, meetings, and support. However, it is not a plug-and-play product: it requires PostgreSQL with pgvector, OpenSearch, Redis, WorkOS, and an OpenAI API key, and the repository is provided as-is without active maintenance.

SpecificationsAI-estimated

Redis6+
Python3.13+
LicenseMIT
Node.js20+
StewardTenant provisioning and lifecycle management
Admin UIReact frontend + Express backend for configuration and onboarding
Slack BotAI-powered question answering in Slack (optional)
EmbeddingsOpenAI API key
MCP ServerModel Context Protocol server for search and document retrieval
OpenSearch2.x
PostgreSQL15+ with pgvector extension
Index WorkerGenerates embeddings and maintains search indices
Ingest WorkerProcesses webhook data and transforms into documents
AuthenticationWorkOS account
Ingest GatekeeperWebhook processor with signature verification
Resource Requirements2.5-8 CPU cores, 4-11GB RAM

Key Features of Grapevine

Unified knowledge index across Slack, Notion, Linear, GitHub, Google Drive, HubSpot, Salesforce and more.
Semantic search powered by AI embeddings to find relevant information across all sources.
Exposes an MCP server for AI assistants like Claude to query company knowledge.
Optional Slack bot for AI-powered question answering directly in Slack.
Self-hostable via Docker Compose or Kubernetes for full data control.
Connector ecosystem with 25+ integrations across communication, project management, docs, code, CRM, design, analytics, meetings, and support.
Custom document upload for sources without a built-in connector.
Multi-tenant architecture with tenant provisioning and lifecycle management.

Use Cases for Grapevine

1

Enterprise Knowledge Search

Provide employees a single searchable interface for scattered knowledge from multiple SaaS tools.

2

AI Assistant Context

Let Claude or other MCP-compatible assistants retrieve company data to answer questions with relevant context.

3

Slack Q&A

Deploy the optional Slack bot so team members can ask questions and get answers directly in Slack.

4

Onboarding and Discovery

Help new hires find docs, tickets, and conversations across tools quickly instead of digging through each app.

5

Customer Support Retrieval

Support agents can search Zendesk, Salesforce, and Intercom together to resolve tickets faster.

6

Engineering Lookup

Search GitHub, GitLab, Linear, and Jira together for code context, issues, and project history.

7

Meeting Intelligence

Index Gong and Fireflies transcripts to revisit decisions, action items, and meeting outcomes.

8

Compliance and Audit

Maintain an aggregated searchable archive of organizational knowledge for internal audit and compliance purposes.

How to use Grapevine?

1

Clone and prepare the repo

Run git clone https://github.com/gathertown/grapevine.git, cd into the directory, install mise, then run mise install and uv sync to set up the Python toolchain.

2

Configure environment variables

Copy .env.example to .env and fill in required values for database, OpenSearch, Redis, OpenAI, WorkOS, and AWS.

3

Start services and initialize the database

Build JavaScript dependencies with cd js-services && yarn install && yarn build && cd .., then run mise dev and mise setup to apply migrations.

4

Connect data sources through the admin UI

Open http://localhost:5173 to configure connectors, onboard your organization, and start ingesting knowledge.

5

Enable MCP for AI assistants

Start the MCP server with uv run python -m src.mcp.server and use scripts/generate_mcp_token.py to create service tokens for assistants like Claude.

Pros & Cons of Grapevine

Pros

  • Unified semantic search across 25+ business tools from one self-hosted platform.
  • MCP server makes company knowledge accessible to AI assistants like Claude.
  • Open source under MIT, with Docker Compose and Kubernetes deployment options.
  • Optional Slack bot provides natural language Q&A directly in Slack.
  • Extensible connector framework for adding custom data sources.

Cons

  • Repository is provided as-is without active maintenance, so updates and support are limited.
  • Requires substantial infrastructure: PostgreSQL, OpenSearch, Redis, WorkOS, and an OpenAI API key.
  • Setup complexity is high for non-technical teams due to Docker, environment variables, and multiple services.
  • No hosted or managed version is mentioned, so users must handle deployment and scaling themselves.

Frequently Asked Questions

What is Grapevine?

Grapevine is an open-source, self-hostable unified knowledge store that ingests information from corporate sources and exposes semantic search via an MCP server.

Which data sources are supported?

It includes connectors for Slack, Gmail, Intercom, Linear, Jira, Asana, Monday, ClickUp, Trello, Teamwork, Notion, Confluence, Google Drive, GitHub, GitLab, HubSpot, Salesforce, Pipedrive, Attio, Figma, Canva, PostHog, Fireflies, Gong, Zendesk, Pylon, and custom uploads.

What are the prerequisites for self-hosting?

You need Docker and Docker Compose, PostgreSQL 15+ with pgvector, OpenSearch 2.x, Redis 6+, an OpenAI API key for embeddings, and a WorkOS account for authentication.

How does the MCP server work?

The MCP server provides tools like semantic_search, keyword_search, get_document, get_document_metadata, and ask so AI assistants like Claude can search and retrieve company knowledge.

Is Grapevine open source?

Yes, Grapevine is released under the MIT License.

Can I deploy Grapevine in production with Kubernetes?

Yes, the repository includes Kubernetes deployment configurations in kustomize, with approximate resource requirements of 2.5-8 CPU cores and 4-11GB RAM.

Is Grapevine actively maintained?

The repository states that it is provided as-is without active maintenance, so users should expect limited ongoing updates and support.

How do I generate service tokens for the MCP server?

Use uv run python scripts/generate_mcp_token.py --tenant-id <tenant_id>, optionally adding --expires-in and --description flags for custom expiry and descriptions.

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