"How to manage Jira tickets effectively" matching MCP servers:

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 assistants to discover and inspect research datasets via a read-only MCP server, offering search, variable listing, and metadata retrieval without reading data files.

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.

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.

MCP server that synthesizes user feedback from multiple sources into actionable insights. Aggregates reviews, support tickets, and survey responses to identify patterns and priorities.

Enables searching live job postings, aggregating labour-market slices, and reporting how long listings have been open, with filters for titles, location, salary, and more.

An MCP server that reads a team's interviews, tickets, and docs to build a model of the product, exposing tools to ask questions, list contradictions and gaps, and draft documents, with all answers citing their source fragments.

Enables offline local LLM analysis of text data via MCP, taking raw text and an instruction to return analysis results without cloud calls.

Simulate hundreds of AI agents to predict how communities react to events and policies. Upload any document (PDF, Markdown, text) and DeepMiro spawns a diverse swarm of AI agents that debate, share, and form opinions — then delivers a calibrated prediction report. Free and open-source.

MCP server for Tracetify — trace how any product actually grew, without leaving Claude Code or Cursor.

Provides read-only access to pre-kick-off football match outcome probabilities and the open record of how those predictions turned out, including match listings, per-match analysis, and aggregate hit rates with baselines. It requires no account or API key and lets users query results by date, week, language, and time zone.

MCP server for the Internet Archive's Wayback Machine. Search archived snapshots, extract page text from a specific date, track how a site has changed over time, check if broken links are recoverable, and perform research across Internet Archive collections.

Webhound is a research engine with an explicit effort control: a prompt defines the investigation and a dollar budget defines how much work it deserves. It returns cited reports or sourced datasets with the working documents, claims, sources, limitations, and evidence pack behind the answer.

Public read-only MCP server for HiBot's AI-visibility knowledge: the ANSWER framework for measuring how AI answer engines surface, recommend, and represent brands, plus audit plans, case studies, and research. Hosted Streamable HTTP endpoint; the repo's Dockerfile bridges stdio via mcp-remote.

Product management copilot that connects Claude to HelpScout support tickets and ProductLift feature requests. Synthesizes customer feedback across sources, scores themes by convergence, and generates prioritized product plans.

Enables AI assistants to manage, report, and analyze Google Ads campaigns securely with encrypted multi-client support, real-time API integrations, and audit trail logging.

Enables sweeping commission and slippage assumptions across backtest results to see how performance degrades, pinpoint the exact cost level where a strategy's edge hits zero, and audit for look-ahead-bias patterns like data leakage and repainting indicators.