Textgraph MCP Server

textgraph

textgraph turns a piece of text into a knowledge graph and answers questions about that graph: what the main topics and clusters are, which connections are missing, and what research questions or ideas those gaps suggest. It can also create a graph in an InfraNodus account, analyse an existing graph by name, and compare several texts through their graphs.

This package is a clean-room rebuild, and a labelled core subset: it covers 12 of the 22+ tools documented for the original InfraNodus MCP server. The omitted tools are listed under "Scope" below.

How it talks to the service

Every tool needs an InfraNodus API key:

export INFRANODUS_API_KEY="your key"
# Optional override (default: https://api.infranodus.com)
export INFRANODUS_API_URL="https://api.infranodus.com"

With no key set, every call fails with an error naming INFRANODUS_API_KEY, before any request is made.

Wire-format note: the original project's README documents the tools and their purposes, not the HTTP wire format. The endpoint shape used here is a documented reconstruction: each tool POSTs its JSON arguments to {INFRANODUS_API_URL}/<tool name> — the tool name with underscores, exactly as listed — with Authorization: Bearer INFRANODUS_API_KEY. Responses are parsed tolerantly: JSON is returned as structured text, a non-JSON body is returned as-is, and an upstream HTTP error is reported with its status and a body excerpt.

Local validation, applied before any request: analyze_text requires at least one of text or url; optimize_text_structure's responseType must be one of response, idea, question, or transcend; and overlap_between_texts / difference_between_texts require at least two texts.

Install

npx @reneturcios/textgraph generate_content_gaps '{"text":"..."}'

Or run the container image:

docker run -i ghcr.io/cloudcorprecords/textgraph

The container defaults to the MCP server. Pass CLI arguments to use it as a CLI instead.

CLI

The CLI mirrors the tools: one subcommand per tool, taking its arguments as a single JSON object.

textgraph generate_knowledge_graph '{"text":"...","graphName":"notes"}'
textgraph analyze_existing_graph_by_name '{"graphName":"notes"}'
textgraph analyze_text '{"url":"https://example.com/article"}'
textgraph optimize_text_structure '{"text":"...","responseType":"idea"}'
textgraph overlap_between_texts '{"texts":["first","second"]}'
textgraph --version

Exit codes: 0 on success, 1 on an API or validation error (the error names the problem), 2 for usage errors.

MCP server

One bin serves both faces. The mcp subcommand starts a stdio MCP server:

npx -y @reneturcios/textgraph mcp

MCP client configuration:

{
  "mcpServers": {
    "textgraph": {
      "command": "npx",
      "args": ["-y", "@reneturcios/textgraph", "mcp"],
      "env": { "INFRANODUS_API_KEY": "your key" }
    }
  }
}

Tools

Scope

Omitted from this core subset: optimize_reasoning, generate_responses_from_graph, develop_conceptual_bridges, develop_latent_topics, develop_text_tool, generate_ontology_graph, analyze_llm_results, merged_graph_from_texts, analyze_google_search_results, analyze_youtube_results, and any tools beyond the fetched README list. The summaries, ideas, and questions these tools return are produced by the upstream InfraNodus service; this package reproduces the tool surface and the request/response handling, not that service's analysis quality.

Development

npm install
npm run build   # tsc -> dist/
npm test        # node test runner over test/*.test.ts, fake fetch only, no network
npm run dev     # run the CLI from source via tsx

License

MIT — see LICENSE.