原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

QueryWeaver

作者:FalkorDB版本 0.0.11i★ –i在你的电脑上运行
注册名称com.falkordb/QueryWeaver

安装

概览

作者提供的说明(英文原文)

An MCP server for Text2SQL: transforms natural language into SQL using graph schema understanding.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: Streamable HTTP
  • 分类: 数据库与数据集

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "queryweaver": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "docker.io/falkordb/queryweaver:0.0.11"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add queryweaver -- docker run -i --rm docker.io/falkordb/queryweaver:0.0.11

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "queryweaver": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "docker.io/falkordb/queryweaver:0.0.11"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "queryweaver": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "docker.io/falkordb/queryweaver:0.0.11"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过域名 falkordb.com 验证(注册中心会核实域名所有权)

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“数据库与数据集”中的其他服务器比较i

  • 星标数多于此分类中其他 952 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 952 个服务器的 0% 更新
  • 基础检查结果等于或优于此分类中其他 952 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

QueryWeaver 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.0.11)于14个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Docker。

有什么可以替代它?

同一分类中有:Supabase, MongoDB MCP Server, Elasticsearch MCP Server

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Supabase

作者:supabase

MCP server for interacting with the Supabase platform

电脑或云端★ 2,993Apache-2.0今天更新
安装

MongoDB MCP Server

作者:mongodb-js

MongoDB Model Context Protocol Server

在你的电脑上运行★ 1,157Apache-2.0前天更新
安装

MCP server for interacting with Elasticsearch

在你的电脑上运行★ 315Apache-2.014个月前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

QueryWeaver (Text2SQL)

REST API · MCP · Graph-powered

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:

Get Started

Docker

💡 Recommended for evaluation purposes (Local Python or Node are not required)

docker run -p 5000:5000 -it falkordb/queryweaver

Launch: http://localhost:5000


Use an .env file (Recommended)

Create a local .env by copying .env.example and passing it to Docker. This is the simplest way to provide all required configuration:

cp .env.example .env

edit .env to set your values, then:

docker run -p 5000:5000 --env-file .env falkordb/queryweaver

Alternative: Pass individual environment variables

If you prefer to pass variables on the command line, use -e flags (less convenient for many variables):

docker run -p 5000:5000 -it \

-e APP_ENV=development \ -e FASTAPI_SECRET_KEY=your_super_secret_key_here \ -e GOOGLE_CLIENT_ID=your_google_client_id \ -e GOOGLE_CLIENT_SECRET=your_google_client_secret \ -e GITHUB_CLIENT_ID=your_github_client_id \ -e GITHUB_CLIENT_SECRET=your_github_client_secret \ -e AZURE_API_KEY=your_azure_api_key \ falkordb/queryweaver

APP_ENV=development is what makes the login work on the plain-HTTP

http://localhost:5000 this command serves. Drop it (or set anything else)

when you put QueryWeaver behind HTTPS, so the session cookie is marked

Secure. See Application environment.

Note: QueryWeaver supports multiple AI providers. You can use OPENAI_API_KEY, GEMINI_API_KEY, ANTHROPIC_API_KEY, or AZURE_API_KEY. See the AI/LLM configuration section for details.

For a full list of configuration options, consult .env.example.

Memory TTL (optional)

QueryWeaver stores per-user conversation memory in FalkorDB. By default these graphs persist indefinitely. Set MEMORY_TTL_SECONDS to apply a Redis TTL (in seconds) so idle memory graphs are automatically cleaned up.

# Expire memory graphs after 1 week of inactivity

MEMORY_TTL_SECONDS=604800

The TTL is refreshed on every user interaction, so active users keep their memory.

MCP server: host or connect (optional)

QueryWeaver includes optional support for the Model Context Protocol (MCP). You can either have QueryWeaver expose an MCP-compatible HTTP surface (so other services can call QueryWeaver as an MCP server), or configure QueryWeaver to call an external MCP server for model/context services.

What QueryWeaver provides

  • The app registers MCP operations focused on Text2SQL flows:
  • list_databases
  • connect_database
  • database_schema
  • query_database
  • To disable the built-in MCP endpoints set DISABLE_MCP=true in your .env or environment (default: MCP enabled).
  • Configuration
  • DISABLE_MCP — disable QueryWeaver's built-in MCP HTTP surface. Set to true to disable. Default: false (MCP enabled).

Examples

Disable the built-in MCP when running with Docker:

docker run -p 5000:5000 -it --env DISABLE_MCP=true falkordb/queryweaver

Calling the built-in MCP endpoints (example)

  • The MCP surface is exposed as HTTP endpoints.
Server Configuration

Below is a minimal example mcp.json client configuration that targets a local QueryWeaver instance exposing the MCP HTTP surface at /mcp.

{

"servers": { "queryweaver": { "type": "http", "url": "http://127.0.0.1:5000/mcp", "headers": { "Authorization": "Bearer your_token_here" } } }, "inputs": [] }

REST API

API Documentation

Swagger UI: https://app.queryweaver.ai/docs

OpenAPI JSON: https://app.queryweaver.ai/openapi.json

Overview

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. In the browser the app uses a signed session cookie established by OAuth or email/password; for CLI and scripts you can use an API token (see tokens routes or the web UI to create one).

Core endpoints

  • GET /graphs — list available graphs for the authenticated user
  • GET /graphs/{graph_id}/data — return nodes/links (tables, columns, foreign keys) for the graph
  • POST /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)

Authentication

  • Add an Authorization header: Authorization: Bearer
Three separate credentials

QueryWeaver keeps its three kinds of "login" independent of one another, so a failure in one never looks like a failure in another:

CredentialWhat it provesWhere it livesDepends on FalkorDB?
Browser loginWho is using the appSigned session cookie, established once by OAuth or a passwordNo, once the process is running
API tokenA script may act as a userToken node in the Organizations graph, sent as Authorization: Bearer …Yes
Data-source connectionAccess to *your* databaseSupplied per request, never storedNo (it is your own database)

Because the browser login is a signed cookie, staying logged in costs no database round trip and survives a FalkorDB outage in an already-running process — you keep your session and only the operations that genuinely need the graph fail. Requests that supply an API token explicitly are always checked against the database and are answered with 503 (not 401) when it cannot be reached, so clients retry instead of re-authenticating.

Note the scope: this is about staying logged in, not about booting. QueryWeaver still connects to FalkorDB at startup and will not start without it, so a restart during an outage is not covered.

A browser login lasts 24 hours by default; set BROWSER_SESSION_TTL_HOURS to change that. Logging out clears the session cookie. No API token is issued to the browser, so there is none to revoke — tokens are created explicitly from the tokens API and revoked there. (A legacy api_token cookie left over from an older release is cleared and revoked on logout too.)

Email signup is verified before the account exists

Signing up with an email address and password does not create an account. The submitted details are parked, a six-digit confirmation code is mailed to the address, and the account — and the session — come into being only when that code is typed back into the signup form. So an address the registrant does not control never becomes an account at all, and there is no half-real user for the rest of the system to reason about.

A code rather than an emailed link, because the code has to come back to the session that submitted the form. A link can be opened by anyone who receives it: a stranger could submit your address with a password of their choosing, and your single click would create an account they knew the password to. Nobody can be signed up by someone else here, because the person who fills in the form is the only one who ever holds both halves.

The code is single-use, expires after 15 minutes and tolerates only a handful of wrong guesses before the pending signup is discarded — a short code is only safe while the number of attempts is small. It is also only redeemable in the browser that submitted the form: each submission mints a ticket that stays in that browser's session, and a code presented without its ticket is refused. Entering it signs the browser in directly: the password was chosen minutes earlier, and asking for it again would prove nothing. A code can be re-sent from the same screen, subject to a per-address rate limit; the send budget is per pending signup, so it starts over once the pending signup expires and an address can always be signed up again later. Typing a code that has expired is not one of the wrong guesses and does not discard anything — the pending signup is left where it is so the same screen can send a fresh code.

In development, a message with no mail server configured is written to the application log instead of being sent, so the flow can be completed by copying the code out of the log. This needs APP_ENV=development — anywhere else an unconfigured process refuses the send rather than logging the code and reporting success. Set MAIL_SERVER (plus MAIL_PORT, MAIL_USERNAME, MAIL_PASSWORD, MAIL_DEFAULT_SENDER) to send for real; any provider with an SMTP endpoint works. EMAIL_VERIFICATION_TTL_MINUTES, EMAIL_VERIFICATION_MAX_ATTEMPTS, EMAIL_VERIFICATION_RESEND_SECONDS and EMAIL_VERIFICATION_MAX_SENDS tune the lifetime and the limits. See .env.example for the full list.

The trade-off of a signed session cookie is that it cannot be revoked from the server before it expires: the TTL bounds the damage, and rotating FASTAPI_SECRET_KEY invalidates every browser login at once. API tokens keep their server-side record and so can still be revoked individually and immediately. Shorten BROWSER_SESSION_TTL_HOURS if you need a tighter window.

Examples

  1. List graphs (GET)

curl example:

curl -s -H "Authorization: Bearer $TOKEN" \

https://app.queryweaver.ai/graphs

Python example:

import requests

resp = requests.get('https://app.queryweaver.ai/graphs', headers={'Authorization': f'Bearer {TOKEN}'}) print(resp.json())

  1. Get graph schema (GET)

curl example:

curl -s -H "Authorization: Bearer $TOKEN" \

https://app.queryweaver.ai/graphs/my_database/data

Python example:

resp = requests.get('https://app.queryweaver.ai/graphs/my_database/data', headers={'Authorization': f'Bearer {TOKEN}'})

print(resp.json())

  1. Load a graph (POST) — JSON payload
curl -H "Authorization: Bearer $TOKEN" -H "Content-Type: application/json" \

-d '{"database": "my_database", "tables": [...]}' \ https://app.queryweaver.ai/graphs

Or upload a file (multipart/form-data):

curl -H "Authorization: Bearer $TOKEN" -F "file=@schema.json" \

https://app.queryweaver.ai/graphs

  1. 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.

Example payload:

{

"chat": ["How many users signed up last month?"], "result": [], "instructions": "Prefer PostgreSQL compatible SQL" }

curl example (simple, collects whole response):

curl -s -H "Authorization: Bearer $TOKEN" -H "Content-Type: ap

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