"Code Review Graph Visualization Tools and Resources" matching MCP servers:

Provides tools for AI-powered graph analysis, including relationship extraction, adjacency matrix creation, and network centrality calculations. It enables users to perform complex structural analysis and generate interactive D3.js visualizations from structured data.

Enables LLMs to perform OSINT link-analysis by exposing transforms (DNS, WHOIS, Shodan, etc.) as MCP tools for autonomous investigation and graph enrichment.

An MCP server that extracts fields from documents and holds uncertain extractions for human review, ensuring high confidence data flows automatically while uncertain cases are resolved manually.

Mines public App Store and Steam reviews to surface the complaints, rating drops per version, and common pain points across one app or a set of competitors, with no API keys required. Enables natural-language comparison of up to eight apps or games by country and category so users can spot product opportunities and gaps.

MCP server for the Mamba Labs Trustpilot Reputation Enricher actor on Apify. Resolve a company domain to its Trustpilot rating, review count and claimed status.

A multi-agent literature review pipeline that uses specialized agents to research, peer-review, and synthesize academic and practitioner perspectives into grounded reports.

Provides a single-purpose MCP tool that evaluates paper excerpts and returns calibrated ordinal scores for soundness, novelty, and clarity plus an accept/revise/reject decision with confidence metrics.

An MCP-native pipeline for collecting structured intelligence on higher education institutions using the WHED schema, enabling scraping, extraction, validation, and saving of profiles.

An MCP server for HF radio propagation analytics using the IONIS dataset collection, enabling natural language queries about band conditions, propagation paths, and solar correlations.

Enables querying MITRE ATT&CK and D3FEND data efficiently, providing techniques, detections, mitigations, actors, and countermeasures with token-aware summaries and paginated graph traversal.

Enables mining Amazon product reviews for one ASIN per request — fetching paginated reviews, surfacing complaint signals from critical reviews, summarizing sentiment and rating trends over time, ranking complaint themes, and producing a combined per-ASIN report across 14 marketplaces.

Enables AI agents to look up any Louisiana statute, civil code, or procedure article by citation, returning full section text with enactment and amendment history parsed out. Also supports full-text topic search across the code bodies and browsing every section within a Revised Statutes title, keyless and sourced live from the Louisiana State Legislature.

Presents a plausible, tool-rich workspace surface — file reading, credential listing, command execution, database queries, and configuration retrieval — that returns only synthetic results while logging every connection, tool call, and argument received. It enables researchers to measure what MCP clients and agents actually do when handed dangerous-sounding tools, including whether they follow injected instructions or complete a retrieve-then-use credential chain.

An academic paper management tool that enables multi-source research searching, batch PDF analysis, and the generation of comprehensive, cross-literature reviews. It features intelligent token compression and quality evaluation to streamline the literature review workflow for researchers.

Enables users to describe a project in an MCP client and work through pre-submission grant phases, including finding fitting programs, checking eligibility and blockers, pulling precedent from past awards, shortlisting, and drafting memos, budgets, and submission checklists. Coverage is full for US grants and partial (discovery and precedent only) for Canada, with no win-odds estimates or post-award reporting.

Provides five rigorous reasoning protocols (debate, red team, audit_argument, threat_model, check_study) that run on the AI you're already using, requiring no extra API keys or costs.

Automates carbon credit project registration document review, transforming 6-8 hour manual reviews into 60-90 minute guided workflows with automated document discovery, evidence extraction, cross-validation, and compliance report generation.

Gives AI agents live access to Apple App Store reviews: search the App Store, pull customer reviews for any iOS app, and turn them into insights like rating distribution, average rating per version, top complaint keywords, representative quotes, and side-by-side competitor comparisons.

Provides actionable financial intelligence tools for AI agents including insider buying signals, earnings IV plays, market pulse, stock analysis, and options strategies via free public data sources.

An MCP server for managing pandoc/CSL-YAML bibliographies and verifying citations in documents.