官方说明7 个来源MCP 服务8 天前
flexorch/flexorch-mcp
Turn business documents (P
在 GitHub 查看 ↗直链 · 无中转页
配置模板（请按你的客户端调整）
claude mcp add flexorch-mcp -- npx -y flexorch-mcp
这是根据仓库名生成的可粘贴骨架，命令行参数与包名请以该项目 README 为准。
- ★ 数取值
- 1 ★ · flexorch/flexorch-mcp · 取自该仓库的 GitHub 页面 · （2026-10-16 20:00:20 核对）
- 来源明细
- 收录自 punkpeye/awesome-mcp-servers 榜单（我们从中收集的条目之一） · 条目类型：MCP 服务
- 收录与活跃
- 收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 7 个来源列出
- 评分构成
- 综合分 703 · 1 ★ · 7 个来源 · mcp
常见问题（答案都来自我们的记录）
怎么安装？
我们【没有】从该仓库取到安装命令（我们的 install 覆盖率只有约 4%）。请看它的 README 或 releases 页。
它适合谁 / 用来做什么？
我们把它归在这些标签下: MCP 服务。标签来自条目自身，不是我们强加的分类。
谁维护它、还在更新吗？
仓库
flexorch/flexorch-mcp；我们收录于 2026-10-09；最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。第三方质量标记
flexorch-mcp
以下摘录自该仓库的 README（片段） · 在 GitHub 读完整 README →
**MCP server for FlexOrch — SDK for machines.**
Connect Claude and other MCP-compatible agents to the FlexOrch document intelligence pipeline. Process documents, extract structured data, detect PII, and export LLM-ready datasets — all through natural language tool calls.
---
What this is
flexorch-mcp is a thin proxy that exposes the FlexOrch API as MCP tools. All processing happens on FlexOrch's managed infrastructure. A FlexOrch account and API key are required.
**For humans writing code:** use flexorch-sdk (Python) or flexorch-sdk-js (TypeScript).
**For agents:** use this package.
---
Tools
| Tool | Description |
|------|-------------|
| document.process | Upload and process a document (PDF, DOCX, TXT, XLSX, HTML, XML, EML, JPG, PNG, TIFF) |
| document.reprocess | Re-queue an already-uploaded document through the pipeline |
| job.status | Poll a processing job until completed or failed |
| job.result | Get structured extracted fields from a completed job |
| dataset.build | Build a structured dataset from a completed execution |
| dataset.search | Semantic search across indexed datasets (Pro+) |
| dataset.export | Export a dataset as JSONL, CSV, JSON, XML, MD, or RAG (LangChain/LlamaIndex chunks) |
| dataset.index | Trigger semantic vector indexing for a dataset (Pro+) |
| dataset.chunks | Retrieve paginated RAG-ready text chunks from an indexed dataset (Pro+) |
---
Installation
Requires Python 3.10+.
---
Configuration
Claude Desktop
Add to your Claude Desktop config file (create it if it doesn't exist):
- macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
- Windows: %APPDATA%\Claude\claude_desktop_config.json
Cursor
Add to your Cursor MCP config:
OpenAI Codex
Add to ~/.codex/config.toml:
Get your API key from app.flexorch.com/settings.
---
Verify connection
---
Example agent workflow
---
Plan limits
All FlexOrch plan limits apply to MCP tool calls. Credits are consumed per document processed.
| Plan | Credits/mo | Semantic search |
|------|-----------|----------------|
| Trial | 1,200 (30 days) | — |
| Starter | 1,200 | — |
| Pro | 6,000 | ✓ |
| Enterprise | Custom | ✓ |
---
Security
- API key is read from the FLEXORCH_API_KEY environment variable — never passed as a tool argument
- No data is stored or cached by this server — stateless proxy
Connect Claude and other MCP-compatible agents to the FlexOrch document intelligence pipeline. Process documents, extract structured data, detect PII, and export LLM-ready datasets — all through natural language tool calls.
---
What this is
flexorch-mcp is a thin proxy that exposes the FlexOrch API as MCP tools. All processing happens on FlexOrch's managed infrastructure. A FlexOrch account and API key are required.
**For humans writing code:** use flexorch-sdk (Python) or flexorch-sdk-js (TypeScript).
**For agents:** use this package.
---
Tools
| Tool | Description |
|------|-------------|
| document.process | Upload and process a document (PDF, DOCX, TXT, XLSX, HTML, XML, EML, JPG, PNG, TIFF) |
| document.reprocess | Re-queue an already-uploaded document through the pipeline |
| job.status | Poll a processing job until completed or failed |
| job.result | Get structured extracted fields from a completed job |
| dataset.build | Build a structured dataset from a completed execution |
| dataset.search | Semantic search across indexed datasets (Pro+) |
| dataset.export | Export a dataset as JSONL, CSV, JSON, XML, MD, or RAG (LangChain/LlamaIndex chunks) |
| dataset.index | Trigger semantic vector indexing for a dataset (Pro+) |
| dataset.chunks | Retrieve paginated RAG-ready text chunks from an indexed dataset (Pro+) |
---
Installation
Requires Python 3.10+.
---
Configuration
Claude Desktop
Add to your Claude Desktop config file (create it if it doesn't exist):
- macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
- Windows: %APPDATA%\Claude\claude_desktop_config.json
Cursor
Add to your Cursor MCP config:
OpenAI Codex
Add to ~/.codex/config.toml:
Get your API key from app.flexorch.com/settings.
---
Verify connection
---
Example agent workflow
---
Plan limits
All FlexOrch plan limits apply to MCP tool calls. Credits are consumed per document processed.
| Plan | Credits/mo | Semantic search |
|------|-----------|----------------|
| Trial | 1,200 (30 days) | — |
| Starter | 1,200 | — |
| Pro | 6,000 | ✓ |
| Enterprise | Custom | ✓ |
---
Security
- API key is read from the FLEXORCH_API_KEY environment variable — never passed as a tool argument
- No data is stored or cached by this server — stateless proxy
- 来源
- awesome · https://github.com/flexorch/flexorch-mcp
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每个标签都能点进去看同类的全部条目。数字是当前库里的真实条数。