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GongRzhe

Langflow Document Q&A Server

by GongRzhe
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Hybrid

Langflow-DOC-QA-服务器

铁匠徽章

由 Langflow 提供支持的文档问答模型上下文协议服务器

这是一个基于 TypeScript 的 MCP 服务器，实现了一个文档问答系统。它通过提供一个简单的接口来通过 Langflow 后端查询文档，从而演示了 MCP 的核心概念。

先决条件

1. 创建 Langflow 文档问答流程

  1. 打开 Langflow 并从“文档问答”模板创建一个新流程

  2. 使用必要的组件（ChatInput、File Upload、LLM 等）配置您的流程

  3. 保存您的流程

图像

2. 获取 Flow API 端点

  1. 点击 Langflow 右上角的“API”按钮

  2. 从 cURL 命令复制 API 端点 URL 示例： http://127.0.0.1:7860/api/v1/run/<flow-id>?stream=false api/v1/run/?stream=false

  3. 保存此 URL，因为API_ENDPOINT配置需要它

图像

Related MCP server: Chalee MCP RAG

特征

工具

  • query_docs - 查询文档问答系统

    • 将查询字符串作为输入

    • 返回来自 Langflow 后端的响应

发展

安装依赖项：

npm install

构建服务器：

npm run build

对于使用自动重建的开发：

npm run watch

安装

要与 Claude Desktop 一起使用，请添加服务器配置：

在 MacOS 上： ~/Library/Application Support/Claude/claude_desktop_config.json在 Windows 上： %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "langflow-doc-qa-server": {
      "command": "node",
      "args": [
        "/path/to/doc-qa-server/build/index.js"
      ],
      "env": {
        "API_ENDPOINT": "http://127.0.0.1:7860/api/v1/run/480ec7b3-29d2-4caa-b03b-e74118f35fac"
      }
    }
  }
}

图像

通过 Smithery 安装

要通过Smithery自动为 Claude Desktop 安装文档问答服务器：

npx -y @smithery/cli install @GongRzhe/Langflow-DOC-QA-SERVER --client claude

环境变量

服务器支持以下环境变量进行配置：

  • API_ENDPOINT ：Langflow API 服务的端点 URL。如果未指定，则默认为http://127.0.0.1:7860/api/v1/run/480ec7b3-29d2-4caa-b03b-e74118f35fac 。

调试

由于 MCP 服务器通过 stdio 进行通信，调试起来可能比较困难。我们推荐使用MCP Inspector ，它以包脚本的形式提供：

npm run inspector

检查器将提供一个 URL 来访问浏览器中的调试工具。

📜 许可证

该项目已获得 MIT 许可。

Available Tools

1 tool
query_docsC

Query the document Q&A system with a prompt

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYesThe query prompt to search for in the documents

TDQS

C2.6/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions querying a 'document Q&A system', which implies a read-only operation, but doesn't specify behavioral traits like response format, error handling, rate limits, or authentication needs. The description is too minimal to provide adequate transparency for safe and effective use.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence: 'Query the document Q&A system with a prompt'. It's front-loaded and efficiently conveys the core action without unnecessary words. However, it could be slightly more informative without losing conciseness, such as by specifying the system's purpose or output type.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (a query tool with no annotations and no output schema), the description is incomplete. It lacks details on what the tool returns, how results are formatted, any limitations, or error conditions. Without annotations or an output schema, the description should provide more context to help the agent understand the tool's behavior and outcomes, but it falls short.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with the 'query' parameter documented as 'The query prompt to search for in the documents'. The description adds no additional meaning beyond this, as it doesn't elaborate on query syntax, examples, or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool 'Query the document Q&A system with a prompt', which provides a basic verb ('Query') and resource ('document Q&A system'), making the purpose somewhat clear. However, it's vague about what 'document Q&A system' entails and doesn't specify the scope or type of documents, leaving room for ambiguity. Without sibling tools, it doesn't need differentiation, but the purpose could be more specific.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description offers no guidance on when to use this tool, such as what types of queries it supports, prerequisites, or limitations. It simply states the action without context, leaving the agent to infer usage from the tool name and parameters alone. This lack of explicit or implied guidelines reduces its helpfulness in selecting the tool appropriately.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool update
    • First observedquery_docs
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

C2.9/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'query_docs' has a clear and distinct purpose for querying documents, so agents cannot misselect among multiple options.

Naming Consistency5/5

The naming is trivially consistent as there is only one tool. It follows a verb_noun pattern ('query_docs'), which is clear and predictable, and there are no other tools to cause inconsistency or mixed conventions.

Tool Count2/5

The tool count is too low for a server with the apparent scope of a 'Document Q&A Server'. A single query tool feels thin and incomplete, as it lacks supporting operations like document upload, management, or retrieval, which are typical for such a domain.

Completeness2/5

The tool surface is significantly incomplete for a document Q&A system. While 'query_docs' allows querying, there are obvious gaps such as no tools for adding, updating, deleting, or listing documents, which are essential for a functional document management and query workflow.

Maintenance

ActivityInactive
ResponsivenessNo issues

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