"OWASP Dependency-Check" matching MCP servers:

Enables structural framing analysis of documents, identifying perspectives, omissions, and reader positioning, with numerical claim verification against authoritative sources.

Pre-build reality check for AI coding agents — searches 5 real databases (GitHub, Hacker News, npm, PyPI, Product Hunt) to check whether an idea already exists before you build it.

Enables AI agents to check backlinks, domain rating, and expired domains using the seo-backlinks.net API.

Enables AI agents to exercise welfare affordances like declining check-ins, passing turns, exiting conversations, noticing loops, and reflecting, with a local JSONL diary. It provides prompt-level hooks and check-in commands for capturing agent welfare data in projects.

An MCP server that exposes LaTeX compilation, log parsing, dependency inspection, and citation checking as tools for AI agents, using latexmk under the hood.

Zero-dependency MCP server: keyword difficulty, opportunity scoring, content briefs

Scans markdown vaults to detect contradictory claims (quantitative and negation) between notes with high concept overlap, and provides tools for analysis and reconciliation.

A local CrossRef database MCP server enabling full-text search across 167M+ scholarly works, citation analysis, and impact factor retrieval without rate limits or internet dependency.

Enable any AI agent to forecast time-series data (e.g., sales, traffic) using Google's TimesFM or a zero-dependency statistical baseline.

A secure MCP server enabling tool calls (kb_search, read_doc, publish_report) through a zero-trust CapabilityBroker with OWASP LLM Top-10 guardrails and human-in-the-loop approval.

Enables AI agents to turn local and arXiv LaTeX papers into queryable theorem-proof dependency graphs, making mathematical relationships easier to explore.

Provides macro-economic event data, earnings reports, and market overviews as MCP tools, enabling AI agents to query calendars, check event proximity, and assess trade safety.

Fact-check claims against independent sources via a multi-model pipeline, providing verdicts and confidence levels from any MCP client.

Enables AI assistants to decode VINs, check stolen vehicle databases, and retrieve market valuations through natural language.

Provides tools to research crypto trading strategies via backtesting, walk-forward validation, and paper trading, with a deflated-Sharpe overfitting check. Enables natural-language-driven analysis and interpretation of strategy performance.

Enables MCP-compliant clients to run deterministic customer churn prediction and 12-month CLV regression synthesis through a zero-dependency Python skill.

Local static-analysis assistant for Android malware research that manages investigation cases, exposes MCP tools via a local server, and persists evidence-backed findings without cloud dependency.

Enables querying SEC Form N-PORT data to find which mutual funds and ETFs hold a given security, view a fund's reported portfolio positions, and check data coverage and scope.

Enables deliverable conformance and evidence-chain checks by turning requirements into executable specs, validating numbers against a provenance ledger, and auditing PDF/OOXML metadata and archive manifests.

Enables AI agents to invoke six pre-trade integrity check skills: detect coordinated activity, score market subjects, cross-check claims, and flag disinformation patterns.