Last updated
March 16, 2026
MCP profile
Falkordb QueryWeaver
An MCP server for Text2SQL: transforms natural language into SQL using graph schema understanding.
Data & AnalyticsPackageociOpen SourceExternal
Visibility
Public
ByRegistry
About This MCP Server
QueryWeaver (Text2SQL)
QueryWeaver is an open-source Text2SQL tool that converts plain-English questions into SQL using graph-powered schema understanding. It helps you ask databases natural-language questions and returns SQL and results.
Connect and ask questions:
QueryWeaver exposes a small REST API for managing graphs (database schemas) and running Text2SQL queries. All endpoints that modify or access user-scoped data require authentication via a bearer token. In the browser the app uses session cookies and OAuth flows; for CLI and scripts you can use an API token (see tokens routes or the web UI to create one).
1) List graphs (GET)
2) Get graph schema (GET)
3) Load a graph (POST) — JSON payload
Or upload a file (multipart/form-data):
4) Query a graph (POST) — run a chat-based Text2SQL request
The POST /graphs/{graph_id} endpoint accepts a JSON body with at least a chat field (an array of messages). The endpoint streams processing steps and the final SQL back as server-sent-message chunks delimited by a special boundary used by the frontend. For simple scripting you can call it and read the final JSON object from the streamed messages.
curl example (simple, collects whole response):
Python example (stream-aware):
Capabilities
GET /graphs — list available graphs for the authenticated userGET /graphs/{graph_id}/data — return nodes/links (tables, columns, foreign keys) for the graphPOST /graphs — upload or create a graph (JSON payload or file upload)POST /graphs/{graph_id} — run a Text2SQL chat query against the named graph (streaming response)Add an Authorization header: Authorization: BearerGraph IDs are namespaced per-user. When calling the API directly use the plain graph id (the server will namespace by the authenticated user). For uploaded files the database field determines the saved graph id.The streaming response includes intermediate reasoning steps, follow-up questions (if the query is ambiguous or off-topic), and the final SQL. The frontend expects the boundary string |||FALKORDB_MESSAGE_BOUNDARY||| between messages.For destructive SQL (INSERT/UPDATE/DELETE etc) the service will include a confirmation step in the stream; the frontend handles this flow. If you automate destructive operations, ensure you handle confirmation properly (see the ConfirmRequest model in the code).
What Problems It Solves
- Create a local .env by copying .env.example and passing it to Docker. This is the simplest way to provide all required configuration:
Specifications
Status
live
Industry
Data & Analytics
Category
General
Server type
Package
Language
oci
License
Open Source
Verified
Yes
Requirements
- Python 3.12+
- uv (Python package manager)
- A FalkorDB instance (local or remote)
- Node.js and npm (for the React frontend)
Hosting
Hosting Options
- Package
API
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1
Install
Install command
oci
docker run -p 5000:5000 -it falkordb/queryweaverPerformance
Usage
Quick Reference
- Name
- Falkordb QueryWeaver
- Function
- An MCP server for Text2SQL: transforms natural language into SQL using graph schema understanding.
- Transport
- Package
- Language
- oci
- Install
- docker run -p 5000:5000 -it falkordb/queryweaver
- Source
- External (Registry)
- License
- Open Source
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