"How to fully utilize Docket application or platform" matching MCP servers:

Enables AI assistants to query, filter, and update job application records, and to analyze skill demand across postings.

Enables AI assistants to interact with the Open Targets Platform API to search and retrieve comprehensive data about target-disease associations, drugs, genes, and drug discovery information through GraphQL queries.

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 AI assistants to directly access quant research knowledge, including factor libraries, strategy backtesting, and research reports, through the MCP protocol.

Enables querying and retrieving materials data from the Materials Project via MCP tools, supporting search, lookup, comparison, and export.

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.

Enables an agent to run ten ready-made research and monitoring workflows — competitor digests, cited reports, paper alerts, market maps, regulatory and due-diligence watches — pulling from Firecrawl, Tavily, GitHub and landing results in Notion, Slack, Google Docs, Sheets and Linear. Fields are filed with the user's own keys held in the operating system keychain, and every action that creates, sends or changes anything is shown and approved first.

Converts PDF files to text for use with MCP-compatible applications like Cursor IDE.

Enables AI agents to resolve Japanese food names to nutrition facts per 100g based on official Japanese food composition data.

The Materials Project MCP Server is server that provides programmatic access to the Materials Project database. It enables LLMs, to search, analyze, and retrieve up to date materials science data.

Enables AI agents to operate DSpace repositories through a typed interface, including SAF package building, metadata editing, scientometric harvesting, open-access PDF downloads, and repository administration.

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

Provides AI assistants with real-time web search, reasoning, and research capabilities through Perplexity's Sonar models and Search API. Supports quick searches, deep research, advanced reasoning, and direct web search with ranked results.

MCP server for Taiwan's agricultural wholesale market real-time price data, providing 6 tools to search products and query trade data at daily, weekly, monthly, yearly granularities, plus cross-market comparisons.

This project implements a Model Context Protocol (MCP) server providing Formula One racing data using the Python FastF1 library. Inspired by an existing TypeScript server, it offers similar F1 data functionalities natively in Python via FastF1.

Provides AI assistants with access to Lumenore's analytics capabilities, enabling natural language queries for data insights, advanced analytics (trends, predictions, correlations, outliers), and real-time data processing with zero persistent storage.

Enables Claude Code to convert PDF files to high-quality PNG images, download academic papers, and batch process PDFs with automatic folder organization.

Converts Digital Object Identifiers (DOIs) to BibTeX format using the official DOI content negotiation API, enabling users to quickly generate bibliography entries for academic papers.

Enables searching and retrieving UK research grants, award values, institutions, and publications from the UKRI Gateway to Research API without authentication.

Enables AI-powered analysis of healthcare market segments, product comparisons, and sales data insights using natural language processing and retrieval-augmented generation.