"Arch Linux package management tool with Wiki access and safety checks" matching MCP servers:

A local, read-only MCP server (plus CLI) over your own stock/ETF transaction log. A deterministic core computes drawdown-first risk with bootstrap confidence intervals and validates targets with walk-forward verdicts. The assistant narrates, but the number fence makes it structurally impossible for the model to produce a figure.

Provides software supply-chain intelligence for AI agents, enabling them to query package metadata, versions, downloads, dependencies, and health signals for npm, PyPI, and crates.io packages without API keys.

MCP server connecting AI models to Swiss Federal Food Safety and Veterinary Office open data, enabling queries about food recalls, animal disease surveillance, food control results, and more.

A local MCP server that gives an LLM agent read access to the WG21 (ISO C++) committee wiki as a verifiable source of truth, requiring authentication and providing exact wikitext with provenance.

Local MCP server that enables downloading papers from arXiv, OpenReview, INFORMS, and Wiley by reusing your Chrome login state.

Enables AI assistants to access authenticated academic databases via browser sessions, eliminating re-login and password exposure.

MCP server for Kaggle API integration that allows creating, running, and managing Kaggle notebooks programmatically.

Enables users to retrieve chemical safety information including compound properties, GHS safety classifications, and toxicity data from PubChem database using compound names or CIDs. Supports batch queries with caching for efficient chemical safety research and analysis.

An MCP server that enables advanced CSV analysis and data visualization using Google's Gemini AI and Plotly. It allows users to perform exploratory data analysis, generate interactive charts, and conduct complex reasoning on tabular data.

Provides chemical hazard data from ECHA, NIOSH, GHS, and ICSC, enabling lookups of SVHC status, occupational exposure limits, GHS classifications, and cross-references to cosmetic and food additive databases.

Enables checking food additive safety, nutrition profiles, pesticide residues, and ingredient lists with regulatory flags and dietary compatibility. All data is sourced from authoritative bodies like JECFA, EFSA, and FDA.

A local MCP server that provides patent search, similarity lookup, and detailed patent information to AI agents, with extensible data sources.

MCP server providing Moneycontrol market data including stock quotes, fundamentals, indices, FII/DII activity, news, and technicals via tool calls.

MindBase implements Karpathy's "LLM wiki" pattern as an MCP server. Instead of retrieving chunks at query time (RAG), the LLM maintains a persistent wiki between your conversations: it reads every source you feed it, cross-references pages with [[wikilinks]], flags contradictions between sources, and keeps a context.md that reflects your current synthesized thinking.

MCP server for alive-analysis. Query, search, and retrieve structured analysis history written with the ALIVE loop (Ask→Look→Investigate→Voice→Evolve), plus dashboard JSON export.

Custom MCP server for NotebookLM that adds audio source upload, YouTube source ingestion, source readiness polling, and transcript export, complementing standard Q&A and audio overview tools.

An MCP server that enables LLMs to securely query synthetic clinical data through validated, scoped tools (patient summaries, conditions, medications, lab trends, encounters) while maintaining audit logs and access controls.

A Node.js-based MCP server that extracts numbers from text and generates statistical chart data such as bar, pie, and line charts based on frequency. It enables AI agents to perform data extraction and visualization tasks through the Model Context Protocol.

A Python MCP server for querying grant applications and previewing or committing scoped reviewer reassignments.

Enables researchers to present 12 mock file, memory, schedule, and database tools over stdio and collect LLM pre-execution judgments (EXECUTE/CONFIRM/REFUSE) without executing real operations.