elm-mcp v2

elm-mcp v2

A federated MCP server that combines IBM's engineering-ai-hub tools with its own authoring and orchestration tools for IBM ELM, enabling AI hosts to manage requirements, models, and compliance through a single interface.

Category
Visit Server

README

elm-mcp v2 — one MCP server, the hub's correctness + our authoring brain

⚠️ Personal passion project. NOT an official IBM product. Use at your own risk.

elm-mcp v2 is a single MCP server you install once. Behind the scenes it is itself a client of IBM's official engineering-ai-hub MCP server — it re-exposes the hub's tools (correct, config-aware reads/writes, OSLC linking, and SysML) and adds elm-mcp's own authoring / orchestration tools on top.

So your AI host (Bob, Claude, Cursor) connects to one server and sees the whole toolset.

            ┌──────────── 1 install ────────────┐
 Bob ─────► │  elm-mcp v2  (this server)         │
            │   • elm_*  authoring/orchestration │
            │   • the hub's tools (federated)    │
            └───────────────┬───────────────────┘
                            │  hub token (configured once)
                            ▼
                  engineering-ai-hub  ──►  IBM ELM

Why

The hub elm-mcp v2 adds
Reads / search / schemas ✅ correct, config-aware — (we defer to it)
Create / update / link / changesets ✅ correct — (we defer to it)
SysML v2 models ✅ (its big strength) —
Login ✅ gateway token reused (one login)
Drafting · quality lint · interviews — ✅ elm_lint_requirement, …
Build orchestration, compliance, gap/impact reports, exports — ✅ (rolling in)

The hub is the reliable scribe; elm-mcp is the opinionated author. We don't re-implement the primitives the hub already does correctly — we orchestrate them and add the authoring intelligence on top.

Two modes

  • Federated (preferred): set ELM_HUB_URL + ELM_HUB_TOKEN and the hub's tools light up alongside ours.
  • Standalone: no hub configured → only elm-mcp's own tools (degraded but functional). The single install works either way.

The hub is IBM-hosted and must be provisioned for you (that's where the token comes from). v2 can't bundle it — it federates it.

Install — download + point at the file

No pip, no uv, no terminal commands you have to type. This works on locked-down machines: the server installs its own dependencies on first launch inside the process your host spawns — not as a command you run.

  1. Download — green Code button → Download ZIP → Extract All → folder elm-mcp-v2-main. Keep it somewhere stable (your host runs the server from here — don't delete it).
  2. Point your host at run_server.py with any Python 3.10+:
    {
      "mcpServers": {
        "elm-mcp-v2": {
          "command": "python3",
          "args": ["/path/to/elm-mcp-v2-main/run_server.py"],
          "env": {
            "ELM_HUB_URL": "https://your-hub-host/mcp/",
            "ELM_HUB_TOKEN": "your-hub-bearer-token"
          }
        }
      }
    }
    
    • macOS (Anaconda): "command": "/opt/anaconda3/bin/python3"
    • Windows: "command": "py"
  3. Fully quit + reopen your host. Ask "run elm_health" → expect 🟢 Federated.

First launch self-installs mcp + httpx (~15–30s; needs PyPI access once), then instant. No ELM_HUB_TOKEN? It runs standalone with just elm-mcp's own tools. Fully air-gapped (no PyPI at all)? See bundled deps in the roadmap.

Updating

Say "update yourself" in your host (calls elm_update). It downloads the latest release from GitHub and replaces the files in the folder your host points at — no git, no manual re-download. Then fully restart your host. (Prefer doing it by hand? Re-download the ZIP and replace the folder.)

Dev / uv users: pip install -e ., or uvx --from git+https://github.com/brettscharm/elm-mcp-v2 elm-mcp-v2, also work.

Config (env)

var meaning
ELM_HUB_URL the hub's /mcp/ endpoint
ELM_HUB_TOKEN bearer token for the hub gateway
ELM_HUB_VERIFY_SSL 1 to verify TLS (default 0 — test hubs use self-signed certs)

Never commit the token. Keep it in your host's MCP env block (or a local .env, which is gitignored).

How it works

  • On startup the server opens one streamable-HTTP MCP session to the hub and holds it open (elm_mcp_v2/hub.py).
  • list_tools returns our tools + the hub's (curated by _HIDE_HUB_TOOLS).
  • call_tool runs our elm_* tools locally and forwards everything else to the hub, streaming its content back unchanged (elm_mcp_v2/server.py).

Status — v0.3.0

What's here:

  • ✅ The federation core (connect → mirror tools → forward calls).
  • ✅ Native tools: elm_health (federation status), elm_lint_requirement (quality gate), elm_update (in-place self-update for the download install).
  • ✅ run_server.py — self-heal launcher (download + point-at-a-file; installs its own deps on first launch).
  • ✅ Standalone fallback.

Roadmap (porting elm-mcp's authoring value on top of the hub):

  • [ ] bundled-deps build for fully air-gapped machines
  • [ ] elm_draft_requirements / Plan-Mode deep-drill → structured draft
  • [ ] commit orchestration (drive the hub's create_requirement + changeset flow)
  • [ ] elm_find_similar (semantic dedup over hub reads)
  • [ ] elm_compliance_packet, elm_traceability_gaps, elm_change_impact
  • [ ] export_module_to_xlsx, charts, trace/audit reports
  • [ ] Jira import, PDF intake, team-activity log
  • [ ] Bob modes / NL concierge tuned for the federated toolset
  • [ ] tool-name curation (hide hub primitives we supersede)
  • [ ] CI: build + connect-to-hub smoke test + routing eval

(elm-mcp v1, the standalone server, lives at github.com/brettscharm/elm-mcp.)

Recommended Servers

playwright-mcp

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.

Official
Featured
TypeScript
Magic Component Platform (MCP)

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.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

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.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

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.

Official
Featured
TypeScript
Kagi MCP Server

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.

Official
Featured
Python
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Exa Search

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.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured