cite-rag-mcp

cite-rag-mcp

A local MCP server for evidence-safe academic citation workflows, including verified-reference retrieval, Zotero duplicate detection and import, and Word export via Pandoc with zotero.lua.

Category
Visit Server

README

cite-rag-mcp

A local MCP server for evidence-safe academic citation workflows:

  • verified-reference retrieval
  • Zotero duplicate detection and DOI import
  • Better BibTeX citekey extraction
  • citekey-constrained writing bundles
  • Word export through Pandoc, zotero.lua, and template.docx

The server supports four workflow modes through the run_reference_workflow tool:

  1. retrieve_only
  2. import_only
  3. export_only
  4. full_pipeline

Safety Rules

  • Never fabricate references, citekeys, DOIs, or citation facts.
  • retrieve_only must not draft prose.
  • import_only must not run open-ended literature retrieval.
  • export_only must not retrieve literature or add references.
  • full_pipeline keeps the end-to-end path, but still cannot bypass verified references.
  • Word export must use Zotero live citations, zotero.lua, and template.docx.

Requirements

  • Python 3.11+
  • Zotero Desktop running locally
  • Better BibTeX for Zotero
  • Pandoc on PATH for Word export

Install Python dependencies:

python -m pip install -r requirements.txt

Codex MCP Configuration

Example config.toml entry:

[mcp_servers.cite-rag-mcp]
command = "python"
args = ["C:\\path\\to\\cite-rag-mcp\\server.py"]
startup_timeout_sec = 20

Adjust the path for your local clone.

Main Tool

Use run_reference_workflow.

retrieve_only

Inputs:

  • citation_need_csv_path, or
  • retrieval_request

Behavior:

  • Searches and ranks literature
  • Verifies DOI metadata
  • Checks Zotero duplicates
  • Imports missing verified DOI items into the selected Zotero collection when needed
  • Returns citekeys

It does not write body text and does not export Word.

import_only

Inputs:

  • doi_list, or
  • title_list plus optional authors_list, or
  • verified_references_csv_path

Behavior:

  • Confirms whether items already exist in Zotero
  • Imports DOI-backed items when needed
  • Returns citekeys or a clear unresolved status

It does not draft body text and does not export Word.

export_only

Inputs:

  • markdown_path, or
  • markdown_content

Behavior:

  • Reads finalized Markdown
  • Removes any <Citation_Reasoning> block before rendering
  • Ensures the references anchor is present
  • Calls Pandoc with zotero.lua and template.docx

It does not retrieve literature and does not add references.

full_pipeline

Inputs:

  • retrieval_request or citation_need_csv_path
  • Optional finalized markdown_path or markdown_content

Behavior:

  • Runs retrieval and verification
  • Produces verified citekeys and a citekey-constrained drafting bundle
  • Optionally exports Word if finalized Markdown is provided

The actual drafting step should still be performed by the orchestrator or a writing skill using the returned citekey bundle.

Notes

  • The included references/custom_journal_catalog.xlsx is used for journal filtering and ranking.
  • The Zotero local connector is expected at http://127.0.0.1:23119.
  • No Zotero credentials or API secrets are required by this server.

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
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

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