经 AI Skill Hub 精选评估,PDF-MCP 获评「推荐使用」。这款MCP工具在功能完整性、社区活跃度和易用性方面表现出色,AI 评分 7.8 分,适合有一定技术背景的用户使用。
PDF-MCP 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
PDF-MCP 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/jztan/pdf-mcp
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"pdf-mcp": {
"command": "npx",
"args": ["-y", "pdf-mcp"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例: 用户: 请帮我用 PDF-MCP 执行以下任务... Claude: [自动调用 PDF-MCP MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入:"列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"pdf-mcp": {
"command": "npx",
"args": ["-y", "pdf-mcp"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
A Model Context Protocol (MCP) server that enables AI agents to read, search, and extract content from PDF files. Built with Python and PyMuPDF, with SQLite-based caching for persistence across server restarts.
mcp-name: io.github.jztan/pdf-mcp
Give your agent surgical access to PDFs instead of flooding context with raw text.
pip install -e ".[dev]"
pip install pdf-mcp
For semantic search (adds fastembed and numpy, ~67 MB model download on first use):
pip install 'pdf-mcp[semantic]'
For OCR on scanned PDFs (requires system Tesseract):
```bash
```
pdf-mcp --help
pre-commit install
Choose your MCP client below to get started:
<details open> <summary><strong>Claude Code</strong></summary>
claude mcp add pdf-mcp -- pdf-mcp
Or add to ~/.claude.json:
{
"mcpServers": {
"pdf-mcp": {
"command": "pdf-mcp"
}
}
}
</details>
<details> <summary><strong>Claude Desktop</strong></summary>
Add to your claude_desktop_config.json:
{
"mcpServers": {
"pdf-mcp": {
"command": "pdf-mcp"
}
}
}
Config file location: - macOS: ~/Library/Application Support/Claude/claude_desktop_config.json - Windows: %APPDATA%\Claude\claude_desktop_config.json
Restart Claude Desktop after updating the config.
</details>
<details> <summary><strong>Visual Studio Code</strong></summary>
Requires VS Code 1.101+ with GitHub Copilot.
CLI:
code --add-mcp '{"name":"pdf-mcp","command":"pdf-mcp"}'
Command Palette: 1. Open Command Palette (Cmd/Ctrl+Shift+P) 2. Run MCP: Open User Configuration (global) or MCP: Open Workspace Folder Configuration (project-specific) 3. Add the configuration:
{
"servers": {
"pdf-mcp": {
"command": "pdf-mcp"
}
}
}
4. Save. VS Code will automatically load the server.
Manual: Create .vscode/mcp.json in your workspace:
{
"servers": {
"pdf-mcp": {
"command": "pdf-mcp"
}
}
}
</details>
<details> <summary><strong>Codex CLI</strong></summary>
codex mcp add pdf-mcp -- pdf-mcp
Or configure manually in ~/.codex/config.toml:
[mcp_servers.pdf-mcp]
command = "pdf-mcp"
</details>
<details> <summary><strong>Kiro</strong></summary>
Create or edit .kiro/settings/mcp.json in your workspace:
{
"mcpServers": {
"pdf-mcp": {
"command": "pdf-mcp",
"args": [],
"disabled": false
}
}
}
Save and restart Kiro.
</details>
<details> <summary><strong>Other MCP Clients</strong></summary>
Most MCP clients use a standard configuration format:
{
"mcpServers": {
"pdf-mcp": {
"command": "pdf-mcp"
}
}
}
With uvx (for isolated environments):
{
"mcpServers": {
"pdf-mcp": {
"command": "uvx",
"args": ["pdf-mcp"]
}
}
}
</details>
For a large document (e.g., a 200-page annual report):
User: "Summarize the risk factors in this annual report"
Agent workflow:
1. pdf_info("report.pdf")
→ 200 pages, TOC shows "Risk Factors" on page 89
2. pdf_search("report.pdf", "risk factors")
→ Relevant pages: 89-110
3. pdf_read_pages("report.pdf", "89-100")
→ First batch
4. pdf_read_pages("report.pdf", "101-110")
→ Second batch
5. Synthesize answer from chunks
Create ~/.config/pdf-mcp/config.toml to restrict which local paths and URL hosts the server will access. The file is optional — if absent, the server is permissive within the built-in SSRF floor (HTTPS-only, blocked private IP ranges).
[paths]
allow = ["~/Documents/**", "/data/pdfs/**"]
deny = ["~/.ssh/**", "~/.aws/**"]
[urls]
allow = ["*.internal.example.com"]
deny = ["untrusted.example.com"]
[limits]
max_response_bytes = 200000
The [limits] block caps text-payload byte size on pdf_read_all and section-granularity pdf_search — see docs/response-limits.md. Rules use shell-glob patterns (* matches across path separators). deny wins when both match. Path matching operates on the resolved path after symlink expansion. A malformed config file prevents the server from starting — it never silently falls back to permissive.
```bash
针对性强的MCP实现,解决AI处理PDF的��际痛点。代码质量和文档完善度关键,适合有MCP基础的开发者。
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
AI Skill Hub 点评:PDF-MCP 的核心功能完整,质量良好。对于Claude Desktop / Claude Code 用户来说,这是一个值得纳入个人工具库的选择。建议先在非生产环境试用,再逐步推广。
| 原始名称 | pdf-mcp |
| Topics | MCP服务器PDF处理Claude集成智能体工具 |
| GitHub | https://github.com/jztan/pdf-mcp |
| License | MIT |
| 语言 | Python |
收录时间:2026-05-24 · 更新时间:2026-05-24 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端