reqif-mcp
An MCP server for requirements engineering that allows loading ReqIF baselines and querying requirements, tracing links, detecting orphans, and diffing baselines using natural language.
README
reqif-mcp
An MCP server for requirements engineering. Load ReqIF / .reqifz baselines (the OMG open standard exported by IBM DOORS, Polarion, Codebeamer, Jama…) and let any MCP client — Claude Desktop, Claude Code, Cursor — query requirements, follow trace links, detect orphans, and diff baselines in natural language.
Requirements management is where automotive, aerospace, rail and defense engineering actually lives, yet the MCP ecosystem has servers for Slack and GitHub and almost nothing for it. This fills that gap.
What it does
Ask your MCP client things like:
- "Which ASIL-D requirements have no verifying test case?"
- "Trace REQ-AEB-001 downstream — what tests cover it, directly or transitively?"
- "Diff baseline v3 against v4: what changed, was added, was removed?"
- "Show me the outline of the AEB specification."
Tools exposed
| Tool | Purpose |
|---|---|
load_reqif |
Parse and index a .reqif / .reqifz file |
search_requirements |
Paginated search over ids, titles, text, attribute values, with optional attribute filter |
attribute_values |
Distinct values of an attribute with counts — the fastest way to discover how a baseline is structured |
get_requirement |
One requirement: all attributes + incoming/outgoing links |
trace_requirement |
Transitive trace links, up/down/both, bounded depth |
find_orphans |
Requirements with no trace links — paginated, filterable (e.g. exclude headings via Object Classification = Requirement) |
diff_baselines |
Added / removed / modified requirements between two baselines, with changed attribute names |
document_outline |
The specification tree (chapters, ordering) |
document_stats / list_documents |
Counts by type, loaded documents |
Install & run
pip install reqif-mcp # or: pip install -e . from a clone
reqif-mcp path/to/baseline.reqifz
Register in Claude Desktop / Claude Code (.mcp.json) — no arguments needed;
load files at runtime with the load_reqif tool:
{
"mcpServers": {
"reqif": { "command": "reqif-mcp" }
}
}
Then, in your MCP client: "Load /path/to/baseline.reqifz and show me the document stats."
CLI arguments are an optional shortcut for small files
(reqif-mcp fixtures/small.reqif); large baselines are better loaded at
runtime so the stdio connection comes up instantly. Unloadable startup paths
log a warning instead of killing the server.
Architecture
.reqif / .reqifz ──▶ parser.py (lxml, namespace-agnostic) ──▶ model.py (dataclasses)
│
MCP client ◀── server.py (FastMCP, stdio) ◀── store.py (in-memory DuckDB: SQL over
requirements / attributes / relations)
Design choices:
- Namespace-agnostic parsing. Real-world ReqIF exports disagree on namespace prefixes and even URI revisions; matching on
local-name()makes the parser tool-vendor tolerant. - Enum values resolved to labels.
ATTRIBUTE-VALUE-ENUMERATIONrefs are resolved throughDATATYPE-DEFINITION-ENUMERATION, so a status readsApproved, notev-4f2a…. - Type-level default values applied. An
ATTRIBUTE-DEFINITIONwith aDEFAULT-VALUEis materialized on every spec-object of that type that doesn't override it — otherwise baseline diffs silently miss defaulted attributes. - DuckDB as the query engine. Orphan detection, transitive tracing and baseline diffs are set operations — SQL expresses them cleanly, and it scales to large baselines without an external service.
- Hardened XML parsing. Entity resolution and network access disabled (XXE-safe).
- XHTML flattened to text. MCP tools serve search and trace; formatting is noise for that job.
Development
pip install -e ".[dev]"
pytest
Tests run against a synthetic ADAS emergency-braking fixture (tests/fixtures/) — no proprietary data anywhere in this repo.
Known limitations
Deliberate scope cuts for v0.1 — the parser extracts all spec-object attributes dynamically (no fixed schema), but:
- Attributes carried by
SPEC-RELATIONs andSPECIFICATIONs themselves are not extracted (only id, type, source/target). RELATION-GROUPs,ALTERNATIVE-IDs and vendorTOOL-EXTENSIONSblocks are ignored.- Datatype constraints (min/max, string length) are not enforced; every value is a string.
- XHTML values are flattened to plain text; embedded objects and formatting are dropped.
Roadmap
- [ ] Semantic search over requirement text (embeddings)
- [ ] MCP resources (expose specifications as browsable resources)
- [ ] Coverage report tool: requirement type A → verifying type B matrix
- [ ] Write-back: export a filtered subset as valid ReqIF
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.