QueryWeaver MCP server
{
"mcpServers": {
"falkordb-queryweaver": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"docker.io/falkordb/queryweaver:0.0.11"
],
"env": {
"OPENAI_API_KEY": "sk-...",
"GEMINI_API_KEY": "<gemini_api_key>",
"ANTHROPIC_API_KEY": "sk-ant-...",
"AZURE_API_KEY": "<azure_api_key>",
"FASTAPI_SECRET_KEY": "<fastapi_secret_key>",
"COHERE_API_KEY": "<cohere_api_key>"
}
}
}
}{
"mcpServers": {
"falkordb-queryweaver": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"docker.io/falkordb/queryweaver:0.0.11"
],
"env": {
"OPENAI_API_KEY": "sk-...",
"GEMINI_API_KEY": "<gemini_api_key>",
"ANTHROPIC_API_KEY": "sk-ant-...",
"AZURE_API_KEY": "<azure_api_key>",
"FASTAPI_SECRET_KEY": "<fastapi_secret_key>",
"COHERE_API_KEY": "<cohere_api_key>"
}
}
}
}{
"mcpServers": {
"falkordb-queryweaver": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"docker.io/falkordb/queryweaver:0.0.11"
],
"env": {
"OPENAI_API_KEY": "sk-...",
"GEMINI_API_KEY": "<gemini_api_key>",
"ANTHROPIC_API_KEY": "sk-ant-...",
"AZURE_API_KEY": "<azure_api_key>",
"FASTAPI_SECRET_KEY": "<fastapi_secret_key>",
"COHERE_API_KEY": "<cohere_api_key>"
}
}
}
}{
"servers": {
"falkordb-queryweaver": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"docker.io/falkordb/queryweaver:0.0.11"
],
"env": {
"OPENAI_API_KEY": "${input:openai_api_key}",
"GEMINI_API_KEY": "${input:gemini_api_key}",
"ANTHROPIC_API_KEY": "${input:anthropic_api_key}",
"AZURE_API_KEY": "${input:azure_api_key}",
"FASTAPI_SECRET_KEY": "${input:fastapi_secret_key}",
"COHERE_API_KEY": "${input:cohere_api_key}"
}
}
},
"inputs": [
{
"id": "openai_api_key",
"type": "promptString",
"description": "Openai api key",
"password": true
},
{
"id": "gemini_api_key",
"type": "promptString",
"description": "Gemini api key",
"password": true
},
{
"id": "anthropic_api_key",
"type": "promptString",
"description": "Anthropic api key",
"password": true
},
{
"id": "azure_api_key",
"type": "promptString",
"description": "Azure api key",
"password": true
},
{
"id": "fastapi_secret_key",
"type": "promptString",
"description": "Fastapi secret key",
"password": true
},
{
"id": "cohere_api_key",
"type": "promptString",
"description": "Cohere api key",
"password": true
}
]
}{
"mcpServers": {
"falkordb-queryweaver": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"docker.io/falkordb/queryweaver:0.0.11"
],
"env": {
"OPENAI_API_KEY": "sk-...",
"GEMINI_API_KEY": "<gemini_api_key>",
"ANTHROPIC_API_KEY": "sk-ant-...",
"AZURE_API_KEY": "<azure_api_key>",
"FASTAPI_SECRET_KEY": "<fastapi_secret_key>",
"COHERE_API_KEY": "<cohere_api_key>"
}
}
}
}file .mcp.json (in your project root)file claude_desktop_config.jsonfile ~/.cursor/mcp.jsonfile .vscode/mcp.jsonfile ~/.codeium/windsurf/mcp_config.jsonversion 0.0.11
What it does
QueryWeaver is an open-source Text2SQL tool that converts natural language questions into SQL by understanding graph-based database schemas. It provides both a REST API and an MCP server interface for developers who need to query databases with natural language.
- Ask a database natural-language questions and receive SQL queries and results without writing SQL manually.
- Integrate Text2SQL capabilities into applications via REST API or MCP endpoints for database querying.
- Maintain per-user conversation memory in graph form to improve query context across multiple interactions.
Tools this server exposes
| Tool | Does |
|---|---|
| list_databases | List available databases accessible to the authenticated user. |
| connect_database | Connect to a database by registering it in QueryWeaver. |
| database_schema | Retrieve the schema of a connected database including tables, columns, and relationships. |
| query_database | Run a Text2SQL chat query against a database and receive SQL and results. |
Before you enable it
An MCP server runs with whatever access you give it. Start with a development account rather than production, and check which tools the server exposes before you let an agent call them unattended.