Docuforge Mcp (docuforge-mcp) MCP Server

@docuforge-mcp/mcp-server npm v0.1.2

Published by @docuforge-mcp — no publish provenance and no public repository, so the publisher could not be verified and the source cannot be independently located.

This package is the **Model Context Protocol (MCP)** server for DocuForge. It exposes the entire DocuForge ecosystem—document creation, academic formatting, AI-driven rewriting, and PDF generation—directly to AI agents and desktop apps like Claude Desktop

Trust grade
A
98/100
Last scanned get badge →
Trust
A · 98/100
Adoption risk for you: the threat score, then adjusted down for blast radius, publisher verification and how much the scan could see. Deterministic; every point is auditable.
Capability
Minimal
Blast radius if it went rogue — what the server’s tools could reach. Independent of trust.
Coverage
Source
How much the scan could actually inspect. Shallow coverage is stated, never hidden.
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A Why this grade threat 100 − adoption risk = 98/100

The grade answers one question — how safe is this server for you to adopt — so it is computed in two auditable stages. Nothing below is an opinion or an LLM's guess; every line is a real term the deterministic engine applied, and the same input always yields the same number.

1. Threat score — 100 − 0 = 100. What the published surface and source actually contain:

The deterministic scan raised no scored threat in the surface it inspected — the threat score stayed at 100. Capability observations and advisory notes are recorded but never lower it.

2. Client adoption risk — 100 − 2 = 98. Three small, subtract-only factors that reflect your risk in adopting it — a clean scan proves less on a powerful, unverified or barely-inspectable package, so the grade says so plainly:

PointsAdoption-risk factor
−2 publisher verification (unlinked) — no provenance/repo link, but the shipped source was fully read

Capability observations and info notes are shown under Findings but never scored. Open any row's finding below for the file, line and evidence behind a deduction.

Findings 0

✓ No findings. The scan raised nothing on this surface — see Coverage for how deep it could look.

Tools 71

Each tool and what it can reach — statically extracted from the published source.

  • add_citationno sensitive capability
  • add_diagramno sensitive capability
  • add_figure_or_tableno sensitive capability
  • add_infographicno sensitive capability
  • ai_compress_sectionno sensitive capability
  • ai_expand_sectionno sensitive capability
  • ai_generate_abstractno sensitive capability
  • ai_generate_diagramno sensitive capability
  • ai_generate_infographicno sensitive capability
  • ai_generate_sectionno sensitive capability
Show 61 more tools ↓
  • ai_paraphrase_sectionno sensitive capability
  • ai_review_documentno sensitive capability
  • ai_rewrite_sectionno sensitive capability
  • ai_suggest_citationsno sensitive capability
  • ai_suggest_keywordsno sensitive capability
  • ai_suggest_referencesno sensitive capability
  • ai_summarizeno sensitive capability
  • ai_translate_documentno sensitive capability
  • append_contentno sensitive capability
  • create_documentno sensitive capability
  • create_ieee_paperno sensitive capability
  • edit_contentno sensitive capability
  • export_bibtexno sensitive capability
  • export_docxno sensitive capability
  • export_htmlno sensitive capability
  • export_markdownno sensitive capability
  • export_pdfno sensitive capability
  • format_citationno sensitive capability
  • format_documentno sensitive capability
  • generate_bibliographyno sensitive capability
  • generate_bug_reportsno sensitive capability
  • generate_competitor_analysisno sensitive capability
  • generate_conference_abstractno sensitive capability
  • generate_documentno sensitive capability
  • generate_edge_casesno sensitive capability
  • generate_feasibility_studyno sensitive capability
  • generate_hackathon_pitchno sensitive capability
  • generate_hldno sensitive capability
  • generate_ieee_paperno sensitive capability
  • generate_literature_reviewno sensitive capability
  • generate_lldno sensitive capability
  • generate_market_researchno sensitive capability
  • generate_prdno sensitive capability
  • generate_project_proposalno sensitive capability
  • generate_qa_checklistno sensitive capability
  • generate_readmeno sensitive capability
  • generate_research_paperno sensitive capability
  • generate_research_proposalno sensitive capability
  • generate_srsno sensitive capability
  • generate_startup_pitchno sensitive capability
  • generate_system_designno sensitive capability
  • generate_systematic_reviewno sensitive capability
  • generate_tech_docno sensitive capability
  • generate_test_casesno sensitive capability
  • generate_thesis_chapterno sensitive capability
  • generate_tocno sensitive capability
  • get_documentno sensitive capability
  • get_document_historyno sensitive capability
  • import_bibtexno sensitive capability
  • import_documentno sensitive capability
  • insert_citationno sensitive capability
  • list_agentsno sensitive capability
  • list_citationsno sensitive capability
  • list_diagram_typesno sensitive capability
  • list_infographic_typesno sensitive capability
  • list_templatesno sensitive capability
  • multi_agent_reviewno sensitive capability
  • remove_citationno sensitive capability
  • restore_versionno sensitive capability
  • search_documentsno sensitive capability
  • validate_ieeeno sensitive capability

What this scan could not see

Versions 1

Scan history per published version. The engine is deterministic — the same version always yields the same score, so a changed score means the package itself changed.

VersionScoreFindingsEngineScanned
v0.1.2 latest A 98/100 0 1.13.0 2026-09-08

Embed this score

Show this server's live Trust Score in your README, docs or website. The badge is served straight from the registry and updates automatically after every rescan — no API key needed. It links back to this page, so anyone who sees the grade can also read the findings behind it instead of taking a number on faith.

MCP Trust Score: A · 98/100
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Verify this score yourself

The score above is reproducible: the same package version always yields the same result. Run it locally or over the free API — no account, no LLM, fully deterministic.

npx mcptrustchecker scan @docuforge-mcp/mcp-server --online

Use the free API → How scoring works

Other implementations of Docuforge Mcp 1

Independent packages implementing the same tool, scanned with the same engine. Compare all 2 side by side →

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