graphrag-ts citation provenance

Name: graphrag-ts citation provenance
Author: sadofriod

by sadofriodversion 0.1.25i★ –iRuns in the cloud

Registry nameio.github.sadofriod/graphrag-ts

Install

Overview

Description from the maker (original English)

Source-tiered retraction and citation judgments for DOIs; abstains when evidence is thin.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi3 of 3 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs in the cloud
Transport: Streamable HTTP
Category: Other
You need to fill in: Authorization

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 3 of 3 passed
Runs on the maker’s server: what you ask it goes through their server.
Can do 3 things (tools) integrity_paper_status, retraction_propagation, integrity_evidence_audit
You fill in yourself: Authorization

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

Runs in the cloudNothing to install; it connects over the internet

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.

Run this in your terminal

claude mcp add --transport http graphrag-ts https://mcp.ashesborn.cloud/mcp --header 'Authorization: Bearer {api_key}'

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "graphrag-ts": {
      "url": "https://mcp.ashesborn.cloud/mcp",
      "headers": {
        "Authorization": "Bearer {api_key}"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "graphrag-ts": {
      "type": "http",
      "url": "https://mcp.ashesborn.cloud/mcp",
      "headers": {
        "Authorization": "Bearer {api_key}"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

Authorization secret HTTP header
Optional. Without a key you get the public read tier: integrity_paper_status answers for free, while retraction_propagation ($0.02) and integrity_evidence_audit ($0.10) return payment_required and ar…

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Tool names and descriptions exactly as the server reported them on Nov 6, 2026. The maker wrote them, not us; we show them as plain text.

integrity_paper_status
Look up one paper by DOI or OpenAlex id and return its identity (title, year, venue) plus every retraction record the graph holds for it, each with its source and source tier: A is an official registry, B an authoritative index, C an aggregator. Use it to check whether a paper is
retraction_propagation
Judge whether a retraction propagates to a paper through its citation graph: retraction evidence is weighted by source tier, the citing context is checked for an acknowledgement, and the tool returns CONTESTED, SUPPORTED or ABSTAINED with the evidence path behind the verdict. Use
integrity_evidence_audit
Audit the evidence behind a paper's retraction picture: every source record with its tier and URI, the dates involved, conflicts between sources (an official registry and an aggregator disagreeing, or a citation acknowledging a retraction the graph does not propagate) and the cov

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account sadofriod, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
✓ Pass
Endpoint responds
Responded in 1137 ms (HTTP 200)
– Not applicable
Sign-in with OAuth
No sign-in needed
✓ Pass
No hidden instructions in tool descriptions
Read 3 tool descriptions and found no hidden instructions to the AI

Compared with others in Otheri

More stars than 0% of the other 32673 servers in this category
Published to the registry more recently than 90% of the other 32673 servers in this category
Basic checks equal to or better than 100% of the other 32673 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is graphrag-ts citation provenance safe?

It passed 3 of 3 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: Authorization

Does it run on my computer or in the cloud?

It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.25) reached the registry 3 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Systemdox

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Spec Driven Development

by formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Runs on your computer★ 440MITUpdated 14 months ago

Install

Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated 2 days ago

Install

Systemdox

by puglieseweb

Your architecture in your agents' context: checks, specs, ADRs and docs over MCP, at write time.

Runs on your computerUpdated today

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

graphrag-ts

Attribution is stored at write time, not asserted at read time.

graphrag-ts is a GraphRAG engine in TypeScript. It builds the knowledge graph in PostgreSQL, keeps source evidence on every node and edge, and answers with retrievable citations — or returns an explicit abstention when the coverage behind an answer is too thin to support it.

Benchmarks / 基准报告

English report · 中文报告

Hosted endpoint / 托管端点

https://mcp.ashesborn.cloud/mcp (anonymous tier: free integrity_paper_status, the two judgments answer with an x402 payment requirement; a keyed session unlocks them) · free DOI status: https://pay.ashesborn.cloud/api/v1/judge/paper?doi= · x402 wire format

Try it in 60 seconds

No install, no API key, no model endpoint. Two ways in:

In a browser: Retraction Status — paste a DOI, get the source-by-source retraction status and the evidence tiers behind it, with no local model and no account.
From the command line:

curl -s 'https://pay.ashesborn.cloud/api/v1/judge/paper?doi=10.1016/S0140-6736(97)11096-0'

The response is the paper plus every retraction record behind it, each with its source_tier and source_uri — the evidence the graph stores, not a model's recollection of it.

Point any Streamable HTTP MCP client at the hosted endpoint (public read tier, 20 requests/minute per IP):

"mcpServers": { "graphrag-ts": { "url": "https://mcp.ashesborn.cloud/mcp" } } }

A bearer API key unlocks the full tool set (graph queries, index jobs, memory writes). The two judgment tools also answer per call without a key via x402 payment ($0.02 / $0.10).

What it does differently

Postgres-native. Graph tables and pgvector live in the database you already operate — no Neo4j sidecar and no second store to keep in sync.
Incremental by construction. Rebuilds reuse unchanged community summaries, so the cost of a refresh tracks the delta rather than the corpus size.
Two retrieval shapes. Local: hybrid vector, keyword and graph retrieval over a community's evidence. Global: Map-Reduce over community summaries for corpus-wide questions.
Explicit abstention. Judgment verdicts carry source tiers and return an abstention when reference coverage is thin, instead of answering from a weak signal.
Evidence at chunk level. Entities and relationships keep the document and chunk they were extracted from, so an answer can be traced back to the text that produced it.

MCP tools

Tool	Access	What it does
`query_graph`	keyed	Local hybrid retrieval against the latest published snapshot in a workspace
`query_graph_global`	keyed	Corpus-wide Map-Reduce retrieval over community summaries
`submit_index_job`	keyed	Queue Markdown from the configured input directory for indexing
`remember_text`	keyed	Queue user-provided text explicitly; never reads chat history
`get_index_job`	keyed	Status and safe error summary for an index job
`integrity_paper_status`	public	Retraction status and identity for a paper
`retraction_propagation`	public / x402	Judge whether retraction evidence propagates to a paper
`integrity_evidence_audit`	public / x402	Audit the evidence path, source tiers and conflicts for a paper

Quick start — self-hosted

MCP with Docker Compose

The Compose stack starts PostgreSQL/pgvector and the MCP service. You must provide reachable chat and embedding endpoints; see the MCP guide for configuration, client setup, and workspace behavior.

cp .env.example .env

Configure the database password and model endpoints in .env.

docker compose up -d --build curl http://127.0.0.1:3000/healthz

Connect an MCP client to http://127.0.0.1:3000/mcp. For the optional local browser showcase, configure the models and run docker compose --profile showcase up -d --build --wait, then open http://127.0.0.1:8080. The showcase is a local demo, not an authentication layer; do not expose it to untrusted users.

Use the library

pnpm install

pnpm run db:generate cp .env.example .env

Configure DATABASE_URL and RAG_* model settings; see the guides below.

pnpm run db:push bun run examples/demo.ts

The library requires Bun, PostgreSQL with pgvector, and compatible chat and embedding endpoints. See the English guide or 中文指南 for environment setup, API examples, adapters, and tuning.

Overview

Markdown ingestion, entity/relationship extraction, and community detection
Full and incremental builds, with unchanged community summaries reused
Hybrid vector, keyword, and graph retrieval, plus corpus-wide Map-Reduce queries
MCP server with isolated workspaces and a local browser showcase

See the architecture guide for the pipeline and module details.

Benchmark

The reported in-corpus run reached 10/12 strict hits and 95.8% combined lexical recall on 12 questions from five indexed chapters. This is a small project benchmark, not human semantic grading or a cross-project comparison. The reports include methodology, per-query results, and limitations.

The English and Chinese reports are linked at the top of this page. To run the three-question Docker smoke benchmark, use pnpm benchmark:docker:quick with the model endpoints configured and loaded. See the MCP guide for prerequisites and the report for benchmark scope.

Listed on

Official MCP Registry — io.github.sadofriod/graphrag-ts
Glama — server rating, plus the connector listing for the hosted endpoint
mcpservers.org

Documentation

docs/architecture.md: architecture and data flow
docs/en-US.md: English user guide
docs/zh-CN.md: Chinese user guide
docs/comparison.md: comparison notes
integrations/mcp/docs/x402-paid-api.md: optional x402 paid query API, dataset bundles
integrations/mcp/docs/hosted-beta.md: hosted pilot operations checklist
integrations/mcp/docs/x402-discovery.md: how agents discover the paid API (Bazaar, .well-known/x402)
integrations/mcp/docs/deploy-x402.md: deploying the paid API on a Docker/Colima host behind Cloudflare Tunnel
CONTRIBUTING.md: contribution guide

Contributing

Contributions are welcome through issues and pull requests. The project is organized around small, testable modules, so the most useful changes usually fit into one of these areas:

graph construction quality
retrieval quality and ranking
namespace isolation
model-loading robustness
documentation and examples

License

MIT

graphrag-ts citation provenance

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

Systemdox

README from the maker

graphrag-ts

Try it in 60 seconds

What it does differently

MCP tools

Quick start — self-hosted

MCP with Docker Compose

Configure the database password and model endpoints in .env.

Use the library

Configure DATABASE_URL and RAG_* model settings; see the guides below.

Overview

Benchmark

Listed on

Documentation

Contributing

License