specir-mcp

specir-mcp

Enables turning technical documents into a structured intermediate representation (SpecIR) and querying it via five MCP tools: specir_resolve, specir_fetch, specir_explain, specir_search, and specir_status. It provides a standardized way to extract, store, and retrieve document sections, tables, figures, entities, and provenance.

Category
访问服务器

README

specir-mcp

English | 简体中文

specir-mcp is a data-neutral framework for turning technical documents into a structured intermediate representation (SpecIR) and querying it through five stable MCP tools.

The repository contains no standards PDFs, extracted specification text, knowledge-base databases, model weights, or vendor-specific protocol tables. All bundled demo content is fictional.

Features

  • Document, section, table, figure, entity, passage, provenance, and edge IR.
  • Extensible domain plugin manifests with dependency-aware loading.
  • PDF outline-based section extraction and reusable structure parsers.
  • SQLite-backed exact lookup, fetch, explanation, search, and status APIs.
  • A five-tool FastMCP surface: specir_resolve, specir_fetch, specir_explain, specir_search, and specir_status.
  • Explicit coverage metadata so missing extraction is not confused with absence from a source document.

Quick start

python -m venv .venv
. .venv/bin/activate
pip install -e ".[test]"

# Generate a small database from the fictional Acme Device Interface fixture.
specir-demo --output data/demo.db

export SPEC_IR_DB="$PWD/data/demo.db"
specir-mcp-server

The same server may be launched from a source checkout:

fastmcp run src/specir/query/server.py

Example MCP calls:

specir_resolve(kind="command", id="A1h", spec="acme-device")
specir_fetch(uid="acme-device:2.1", include_xrefs=true)
specir_explain(name="Read Telemetry", kind="command", spec="acme-device")
specir_search(query="telemetry", spec="acme-device")
specir_status()

When a database contains one document, spec="auto" selects it. With multiple documents, exact lookups return candidates and request an explicit spec.

Using your own data

Create a database with specir.query.schema.create_database, then insert documents and entities using the schema documented by the Python dataclasses. Set SPEC_IR_DB to that database before starting the server. The framework never downloads or bundles source documents.

The optional PDF extractor can build coordinate-clipped section records:

from specir.extractors.pdf import build_section_tree

sections = build_section_tree("my-spec", "path/to/your-document.pdf")

You are responsible for having permission to process and store the documents you supply.

Development

pytest
python -m build

The tests create temporary synthetic databases and do not require external specifications or network access.

License

Apache License 2.0. See LICENSE.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选