Textgraph

io.github.CloudCorpRecords由 GitHub 帳號 CloudCorpRecords 發布v0.1.0更新於 Nov 3, 2026

通過InfraNodus將文字轉化為知識圖譜:主題、聚類、空白和研究思路。

AI 翻譯由 AI 模型根據下方的原文描述翻譯,可能有誤。

原文描述

Text to knowledge graphs: topics, clusters, gaps, and research ideas via InfraNodus.

已驗證STDIO僅桌面知識與記憶

概覽

Textgraph 的本機 MCP 服務;無需登入;STDIO。

暫無 AI 概覽:以下資訊來自註冊中心條目和服務本身。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Textgraph,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

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:

bash
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

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

Or run the container image:

bash
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.

bash
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:

bash
npx -y @reneturcios/textgraph mcp

MCP client configuration:

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

Tools

ToolInputWhat it does
generate_knowledge_graphtext (required), graphNameConvert text into a knowledge graph: topics, concepts, relationships, clusters.
analyze_existing_graph_by_namegraphName (required)Retrieve and analyze an existing graph from the account.
analyze_texttext and/or url (at least one required, validated locally)Analyze a text or URL: topics, clusters, statements, graph structure.
generate_content_gapstext (required)Detect missing connections and underexplored topics in a text.
generate_topical_clusterstext (required), generateTopicalSummariesTopics and keyword clusters from text.
generate_contextual_hinttext (required)Topical overview of a text to augment LLM responses.
generate_research_questionstext (required)Research questions bridging content gaps.
generate_research_ideastext (required)Research ideas based on content gaps.
optimize_text_structuretext (required), responseType (one of response / idea / question / transcend, validated locally)Bias/coherence analysis.
create_knowledge_graphtext (required), graphName, statements, categoriesCreate a graph in the account from text and return its link.
overlap_between_textstexts (array, at least 2, validated locally)Similarities between texts via their graphs.
difference_between_textstexts (array, at least 2, validated locally)What's in the other texts but not the first.

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

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

License

MIT — see LICENSE.

來源:README.md,提交 c6d34a4

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v0.1.0最新Nov 3, 2026

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