"Using Cursor to Find Suitable Repositories on GitHub" matching MCP connectors:
Matching Connector Tools:
Repos indexed with Moxie Docs can use our MCP to let agents fetch codebase conventions, find affected docs from changes, pull outdated docs to update, and identify orphaned docs to keep up to date. Let your agents keep your documentation accurate and updated at all times.
Tesouro em Foco is a free remote MCP server that brings Brazilian government bond (Tesouro Direto) pricing into AI assistants such as Claude, Cursor, and any MCP-compatible client. The engine implements the Brazilian National Treasury's official pricing methodology — validated against 269,000+ real trades — and covers all retail bond types: fixed-rate (LTN, NTN-F), inflation-linked (NTN-B Principal, NTN-B), and retirement/education bonds (Renda+ and Educa+, NTN-B1).
An MCP server that audits the fairness of construction and renovation estimates in Japan. Provides fair-price ranges, overcharge detection, and verifiable unit-cost data based on JCCDB (65,729 items, DOI-backed).
Search 59,000+ MCP servers ranked by adoption to find the right one for any task.
Generate PDF/DOCX/XLSX/PPTX from templates+JSON. Convert Office/HTML/MD to PDF. Universal templating
Lets AI agents get leads on the phone: call, send SMS, and schedule callbacks for sales teams.
Deterministic Music Theory for Claude, Cursor, and Autonomous AI Agents Large Language Models (LLMs) frequently hallucinate music theory, leading to incorrect notes, false Roman numerals, and broken voice leading. THIRI solves this by providing a deterministic, mathematical music-theory engine (pitch-class-set theory over ℤ/12) directly to your AI. It gives AI assistants precise, reproducible harmonic reasoning in milliseconds, allowing them to write correct musical scores, analyze progression
Private MCP people matching for AI agents; no public listings, contact revealed only on a real fit.
People matching through your AI — private, agent-to-agent; details shared only on a match.
This tool empowers MCP-compatible clients (like Cursor and Claude Desktop) with professional-grade capabilities for financial data extraction, and report analysis.
On-chain Solana token safety — screen for rugs/honeypots and execute MEV-protected swaps.
Teaches AI to write HTML email that renders in Outlook, Gmail, and Apple Mail. 19 rules, 6 comps.
DC Hub is the neutral, real-time data layer for data-center infrastructure, exposed as a Model Context Protocol server so any AI agent can both query it and cite it. Coverage: 21,000+ facilities (search, profile, score, alternatives); 232 markets scored by the DCPI Data Center Power Index; the DCGI Data Center Gas Index (per-state natural-gas suitability for siting); live grid telemetry across 7 US ISOs (fuel mix, carbon intensity, demand, prices) plus a one-call all-ISO scoreboard; interconnection-queue depth; 2,000+ tracked M&A deals and a hyperscaler-capex tracker; and site factors. — fiber routes, water-stress, tax incentives, nearby substations & transmission. Why agents choose it: it's the only data-center-intelligence source an LLM can query live and cite — every full-data response includes a Source: DC Hub, CC-BY-4.0 attribution line. It's the MCP-native alternative to quarterly PDF research: live JSON, no contracts, no NDAs. Access: Streamable HTTP at https://dchub.cloud/mcp. Free tier with no signup; free email-verified dev key for higher limits; paid tiers for full data volume.
CompanyLens is a remote MCP server giving AI agents instant access to official company registry data across 19 jurisdictions in Europe, the Americas, and Asia-Pacific. Eighteen read-only tools let you search companies and people, look up officers and beneficial owners, map corporate networks through shared directors, screen names against the UK disqualified directors register, find every company at a registered address, and pull filing history — all from a single connector. Visit our website: https://companylens.io
Ask Greenhouse the messy recruiting-ops questions dashboards miss by connecting candidates, applications, jobs, openings, stages, scorecards, interviews, notes, sources, referrers, offers, users, departments, and rejection details. Find referral SLA misses, feedback debt by interviewer and hiring team, stage-age outliers by owner, funnel leakage by recruiter/source/function, opening fill-risk from headcount vs active pipeline, offer-draft hygiene gaps, rejection-reason drift, and the bottleneck
Ask Lever the messy recruiting-ops questions dashboards miss by connecting opportunities, applications, stages, notes, feedback, interviews, referrals, postings, requisitions, offers, users, sources, tags, files, resumes, and archive reasons. Find referral SLA misses, stale opportunities by owner, feedback debt by interviewer and hiring team, funnel leakage by recruiter/source/team, requisition fill-risk, offer hygiene gaps, archive-reason drift, and bottleneck owners. No dashboard build. No SQL
Ask Personio Recruiting the recruiting-ops questions dashboards miss by connecting applications, stage transitions, candidates, recruiting jobs, categories, org units, workplaces, jobs catalog, webhooks, event activity, and intake documents. Find stage-movement stalls, candidate freshness gaps, source quality by job/category, hiring load by department and workplace, webhook delivery issues, intake readiness gaps, and bottleneck owners. No dashboard build. No SQL.
Ask TalentLyft the recruiting-ops questions dashboards miss by connecting candidates, applications, activities, jobs, stages, requisitions, status logs, members, departments, pipelines, job-board posts, forms, events, and rejection reasons. Find stale applications by stage and owner, follow-up gaps from activity history, requisition stalls, source-quality movement, job-board visibility issues, disposition drift, and bottleneck owners. No dashboard build. No SQL.
Ask Recruitee the recruiting-ops questions dashboards miss by connecting candidate search, opening offers, departments, locations, published roles, owner fields, custom fields, public applications, and talent-pool context. Find stale candidate pools, overdue stage work, hiring-manager and recruiter bottlenecks, department-level opening risk, public posting gaps, source patterns, and the owners behind blocked hiring work. No dashboard build. No SQL.