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MCP server · Developer Tools

Ld MCP

by · github.com/robsyc/ld-mcp

Linked Data MCP - A Python-based MCP server for QA over W3C semantic web and linked data standard specifications: RDF, RDFS, SPARQL, OWL, SHACL and more

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About Ld MCP

Ld MCP is an MCP server published by robsyc in the Developer Tools category: linked Data MCP - A Python-based MCP server for QA over W3C semantic web and linked data standard specifications: RDF, RDFS, SPARQL, OWL, SHACL and more.

The repository has 25 stars and 1 forks, with the last commit yesterday. Recent commit activity is the strongest signal that reported issues will get attention.

Install

From source
git clone https://github.com/robsyc/ld-mcp

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Tools (5)

get_resource(ns_key, resource)Get Turtle definition of a resource

Parameters not published.

get_section(spec_key, section_id)Get markdown content for a section

Parameters not published.

list_resources(ns_key)List classes/properties in a namespace

Parameters not published.

list_sections(spec_key, depth?)Get TOC with section IDs

Parameters not published.

list_specifications(family?)Browse spec families (RDF, SPARQL, OWL, SHACL, SKOS, etc.)

Parameters not published.

Ask AI

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Security checks

Static checks derived from the repository 4 days ago. Heuristics on the source, not an audit.

  • ✓README presentThe repository ships documentation.
  • ✓License declaredUsable under a stated license.
  • ✓Tests presentA test suite exists in the repository.
  • ✓Dependencies pinnedA lockfile pins dependency versions.
  • ✓No dynamic code executionSource scan found no eval, dynamic Function, or shell execution.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

README

CI

Linked Data MCP

MCP server for AI agents to progressively access W3C Semantic Web specifications. Instead of dumping entire spec docs into the rotting context, it serves them section-by-section. Your AI can now look up that one SHACL 1.2 property it keeps forgetting about without burning 100k tokens.

Supported Standards

Family Specifications Namespace
RDF RDF 1.1/1.2 Primer, Concepts, Semantics, Turtle, TriG, N-Triples, N-Quads, JSON-LD rdf:, rdfs:
SPARQL SPARQL 1.1/1.2 Query, Update, Overview -
OWL OWL 2 Primer, Overview, Syntax, Profiles, RDF Mapping owl:
SHACL SHACL 1.1/1.2 Core, Advanced Features, SPARQL, Node Expressions, Rules, UI sh:
SKOS SKOS Primer, Reference skos:
PROV PROV Primer, Data Model, Ontology prov:
TIME OWL-Time time:

See the index.yaml file for the full list of specifications and namespaces. Please feel free to submit a PR to add more specifications and parsers.

Quick Start

Option 1: FastMCP Cloud (Recommended)

Fork the repo, configure the index.yaml and deploy to your own fastmcp.cloud instance (free for personal use). Afterwards, you can use their web ui to connect your agentic coding tool (e.g. Cursor, Claude Desktop, etc.) to the MCP server.

Option 2: Install as a tool

Prerequisites: Python 3.11+ and uv.

git clone https://github.com/robsyc/ld-mcp && cd ld-mcp
uv tool install .

Then add to your .cursor/mcp.json or Claude Desktop config:

{
  "mcpServers": {
    "ld-mcp": {
      "command": "ld-mcp"
    }
  }
}

Option 3: Run with uv

git clone https://github.com/robsyc/ld-mcp && cd ld-mcp
uv sync

Add to your .cursor/mcp.json or Claude Desktop config:

{
  "mcpServers": {
    "ld-mcp": {
      "command": "uv",
      "args": ["tool", "run", "ld-mcp"]
    }
  }
}

Available Tools

Tool Description
list_specifications(family?) Browse spec families (RDF, SPARQL, OWL, SHACL, SKOS, etc.)
list_sections(spec_key, depth?) Get TOC with section IDs
get_section(spec_key, section_id) Get markdown content for a section
list_resources(ns_key) List classes/properties in a namespace
get_resource(ns_key, resource) Get Turtle definition of a resource

Configuration

Variable Description Default
SPEC_VERSIONS Filter by version (e.g., "1.2") All
CACHE_TTL Cache TTL in seconds 86400 (24 hours)
INDEX_PATH Path to a custom index.yaml Bundled default

Development

uv sync --group dev

# Validate all specs/namespaces
uv run pytest tests/test_index.py -v

# Lint
uv run ruff check src/ tests/

# MCP Inspector (web UI for testing tools)
uv run fastmcp dev inspector src/ld_mcp/server.py:mcp

Adding Specifications

  1. Add entry to src/ld_mcp/index.yaml
  2. Run uv run pytest tests/test_index.py -v -k "your_spec_key"
  3. Push to main — CI validates automatically

Acknowledgments

README fetched from the repository 4 days ago. The original is authoritative.

Questions

About Ld MCP

How do I install Ld MCP?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Ld MCP safe to use with an AI agent?

Its trust score is 64 out of 100 (good). It passes 5 of the 6 static security checks run so far; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Ld MCP still maintained?

Yes — the last commit was yesterday. The repository has 25 stars and 1 forks.