"Connecting Feishu (Lark)" matching MCP connectors:
GET /v1/connectors — MCP directory API referenceMatching Connector Tools:
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 Factorial ATS the recruiting-ops questions dashboards miss by connecting applications, phases, candidates, sources, feedback, evaluation forms, job postings, messages, questions, answers, and rejection reasons. Find applications aging in phase, feedback debt by role and posting, source-quality gaps, rejected-candidate hygiene, incomplete application data, hiring-stage bottlenecks, and owner queues. No dashboard build. No SQL.
Ask Teamtailor the recruiting-ops questions dashboards miss by connecting candidates, job applications, jobs, stages, scorecards, referrals, activities, notes, interviews, todos, users, teams, departments, locations, requisitions, and offers. Find stuck applications by owner, referral follow-up misses, feedback gaps by hiring team, source quality by job, stage-age outliers, offer-state hygiene, and bottleneck owners. No dashboard build. No SQL.
Search Laravel jobs, remote roles, Laravel news, and package releases in real time.
Baselight’s MCP server lets you seamlessly integrate your favourite applications with the Baselight platform. By connecting to the MCP server, you can browse, discover, and query 70,000+ datasets and 450+ billion rows directly from your preferred environment—whether you’re building, analysing, or exploring.
Search 161 dark/deep data sources across 25+ domains that Google can't reach. 6-step pipeline methodology for intelligence gathering. Streamable HTTP endpoint.
The Needle MCP server enables semantic search on documents stored in files like PDFs, DOCX, and XLSX by connecting AI applications to external data sources. It provides capabilities to create and manage document collections, perform natural language searches on stored content, and retrieve relevant information without requiring exact keyword matches.
