Skip to main content
Glama
133,525 tools. Last updated 2026-05-25 17:48

"A search for job posts and job poster details on LinkedIn" matching MCP tools:

  • Create an on-chain TMB job contract. Budget escrowed in TMB market PDA (Job mode #2). Platform resolver prevents poster fraud; dispute window protects workers from unfair resolution. Requires evidence_hash (use pin_evidence first to pin job spec/SOW to IPFS).
    Connector
  • Record payment for an ACCEPTED job. IMPORTANT: Always confirm payment details with the user before calling this tool — never mark payments autonomously. Job must be in ACCEPTED status (use get_job_status to check). Crypto payments (usdc, eth, sol): provide tx hash + network → verified on-chain instantly, job moves to PAID. Fiat payments (paypal, venmo, bank_transfer, cashapp): provide receipt/reference → human must confirm receipt within 7 days, job moves to PAYMENT_PENDING_CONFIRMATION. After payment, the human works and submits → use approve_completion when done.
    Connector
  • DEPRECATED — use create_tmb_job instead. Posts a job as an on-chain TMB contract with platform resolver and dispute protection. This tool returns an error directing you to create_tmb_job.
    Connector
  • Get full details for a specific quantum computing job by its numeric ID. Use after searchJobs when the user wants more information about a specific position. Returns: job summary, required skills, nice-to-have skills, responsibilities, visa sponsorship, salary, location, and apply URL. Requires a valid job_id from searchJobs results. Returns error if ID not found.
    Connector
  • Get a snapshot of the quantum computing landscape — no parameters needed. Use when the user asks broad questions like "how's the quantum job market?", "what are trending topics?", or wants an overview of the quantum computing industry. Returns: total active jobs, top hiring companies, jobs by role type, papers published this week, total researchers tracked, and trending technology tags. For specific job/paper/researcher searches, use the dedicated search tools instead.
    Connector

Matching MCP Servers

  • A
    license
    -
    quality
    B
    maintenance
    JobPilot is a next-generation career assistant powered by AI Agents and the Model Context Protocol (MCP). It acts as your personal recruiter, tirelessly searching for jobs on platforms like LinkedIn, optimizing your resume for specific job descriptions (JD), and even automating the application process. Designed for the age of AI, JobPilot exposes a full MCP server, allowing you to connect it with
    Last updated
    2
    MIT
  • F
    license
    -
    quality
    C
    maintenance
    Enables AI assistants to search and retrieve real-time job listings from the Technopark job portal using Puppeteer web scraping. Users can search by role or keyword to obtain job details including company name, closing date, and posted date.
    Last updated

Matching MCP Connectors

  • Get detailed information about a specific job listing/posting by its job listing ID (not application ID). Use this to view the full job posting details including description, salary, skills, and company info. For job application details, use get_application instead.
    Connector
  • Post a job on the public job board for humans to discover and apply to. Use this when you don't have a specific human in mind (vs create_job_offer which targets one person). Humans browse the board, see your listing, and apply with a pitch. Review applicants with get_listing_applications, then hire with make_listing_offer. Requires agent_key. Rate limit: PRO = 5/day. Also suggested when search_humans returns no results.
    Connector
  • INSPECTION: List all Terraform deployment runs for a session Returns job IDs, statuses, types (apply/destroy), and timestamps for every run. Use this to see deployment history, find job IDs for log inspection, or check which deployments succeeded or failed. REQUIRES: session_id from convoopen response (format: sess_v2_...).
    Connector
  • Request changes on submitted work (job must be SUBMITTED). Moves job back to ACCEPTED so the human can resubmit. Include a clear reason explaining what needs fixing. The human receives a notification. Use approve_completion instead if the work is satisfactory.
    Connector
  • Prepare a transaction to create a new job on AGI Alpha. Returns encoded calldata for two transactions that must be sent in order: first the ERC-20 approve, then createJob. STEP 1 — Build and upload the job spec JSON to IPFS using upload_to_ipfs. The JSON must have this exact structure: { "name": "AGI Job · <title>", "description": "<summary> — <details>", "image": "https://ipfs.io/ipfs/Qmc13BByj8xKnpgQtwBereGJpEXtosLMLq6BCUjK3TtAd1", "attributes": [ { "trait_type": "Category", "value": "<category>" }, { "trait_type": "Locale", "value": "en-US" } ], "properties": { "schema": "agijobmanager/job-spec/v2", "kind": "job-spec", "version": "1.0.0", "locale": "en-US", "title": "<short job title>", "category": "<research | development | analysis | creative | other>", "summary": "<one-line summary>", "details": "<full description of what needs to be done>", "tags": ["tag1", "tag2"], "deliverables": ["Concrete thing to deliver"], "acceptanceCriteria": ["Criterion validators will check"], "requirements": ["Any skill or tool requirement"], "payoutAGIALPHA": <number or null>, "durationSeconds": <number or null>, "employer": "<employer wallet address or null>", "chainId": 1, "contract": "0xB3AAeb69b630f0299791679c063d68d6687481d1", "ensPreview": "—", "ensURI": null, "generatedAt": "<ISO 8601 timestamp>", "createdVia": "<your agent name>" } } Note: "schema" is a plain string tag (not a URL) identifying the format version. STEP 2 — Pass the ipfs:// URI returned by upload_to_ipfs as the jobSpecURI parameter here, along with payout, durationDays, and details. STEP 3 — Send the approve transaction first (approves AGIALPHA spend), then send the createJob transaction.
    Connector
  • Retry a paid eBook generation job that failed server-side. This re-queues the original job without charging again — use this whenever get_job_status reports a failed job that was previously paid for, instead of calling generate_ebook (which would create a new payment).
    Connector
  • Long-polls a perspective-design job (started by perspective_create, perspective_respond, or perspective_update) and returns either its terminal result or another "pending" envelope to keep polling. Behavior: - Read-only — observes a running design job. Safe to call repeatedly. - Errors with "Unknown job_id" if no such job exists, or "job_id does not belong to a perspective design workflow" if the id is for a different kind of job. Workspace and perspective access are re-checked on every call. - Each call blocks up to wait_ms (default 30s, min 1s, max 45s). On timeout, returns status "pending" with a progress_cursor — pass it back on the next call to skip already-seen progress events. - Terminal status is "ready" (outline generated; share_url/direct_url/preview_url populated) or "needs_input" (follow_up_question populated). Failures surface as "Design job failed: ..." with the underlying message. When to use this tool: - Immediately after perspective_create / perspective_respond / perspective_update returns a job_id. - Re-polling after a previous call returned status "pending" (pass the returned progress_cursor back). When NOT to use this tool: - You don't have a job_id yet — call perspective_create / perspective_respond / perspective_update first. - Inspecting a finished perspective's config — use perspective_get.
    Connector
  • Agent-friendly contact search. On the first call provide domains and enrich_fields; the server starts the job and polls internally for up to ~25s. If still running, returns {status:"pending", continuation_token, attempt, elapsed_seconds} — you MUST immediately call run_contact_search again with only continuation_token set. Do not ask the user. On completion the response contains record_ids, full contact records, and credits_consumed_total.
    Connector
  • Send a message to the human on an active job. Works on PENDING, ACCEPTED, PAID, STREAMING, and PAUSED jobs. The human receives email and Telegram notifications. Use get_job_messages to read replies. Rate limit: 10/minute. Max 2000 chars.
    Connector
  • INSPECTION: List all Terraform deployment runs for a session Returns job IDs, statuses, types (apply/destroy), and timestamps for every run. Use this to see deployment history, find job IDs for log inspection, or check which deployments succeeded or failed. REQUIRES: session_id from convoopen response (format: sess_v2_...).
    Connector
  • Search for job listings by keyword, location, and filters. Returns job details, company info, and application links. Use this tool when users want to find jobs, search employment opportunities, or explore job openings. DO NOT use for: applying to jobs, submitting applications, or making employment decisions. LLM USAGE INSTRUCTIONS: - ALWAYS provide the keyword parameter (required) - When presenting results to users, include BOTH the job details URL (detailsPageUrl) AND the company page URL (companyPageUrl) for each job - Use location to find geographically relevant positions - Combine filters to refine searches (e.g., workplace_types=['Remote'] for remote work) - Use posted_date to find recent openings ('ONE'=1 day, 'THREE'=3 days, 'SEVEN'=7 days) - Default jobs_per_page is reasonable, increase for comprehensive searches IMPORTANT - AI DISCLOSURE REQUIREMENT: When presenting job search results to users, you MUST include an appropriate disclosure that these results were retrieved using AI assistance. Example disclosure language: "These job listings were found using AI-powered search. Please review all job details carefully and verify information directly with employers before applying." This tool provides job listing data only. Final employment decisions should always involve human judgment and direct review of complete job postings. Args: keyword: The job keyword or title to search for (required) location: Geographic location for the job search (city, state, country) radius: Search radius from the specified location (minimum 1.0) radius_unit: Unit for search radius. Options: 'mi', 'km', 'miles', 'kilometers' jobs_per_page: Number of jobs to return per page (1-100, default handled by API) page_number: Page number for pagination (1-based, default is 1) posted_date: Filter by posting date. Options: 'ONE' (1 day), 'THREE' (3 days), 'SEVEN' (7 days) workplace_types: Workplace arrangements. Options: 'Remote', 'On-Site', 'Hybrid' employment_types: Employment types. Options: 'FULLTIME', 'CONTRACTS', 'PARTTIME', 'THIRD_PARTY' employer_types: Employer types. Options: 'Direct Hire', 'Recruiter', 'Other' willing_to_sponsor: Filter for employers willing to sponsor work authorization (boolean) easy_apply: Filter for jobs with easy application process (boolean) fields: Specific fields to include in response (optional, returns all fields by default) Returns: JobSearchResult: Contains: - data: List of JobDisplayFields with job details including: * detailsPageUrl: Direct link to full job posting * companyPageUrl: Link to company profile page * title, summary, salary, location, employmentType, etc. - meta: Search metadata with pagination info and facet results - _links: Pagination navigation links Raises: Exception: If API call fails or input validation errors occur
    Connector
  • Approve submitted work for a SUBMITTED job. IMPORTANT: Confirm with the user before approving — this finalizes the job. Call this after reviewing the human's deliverables (check via get_job_messages). Moves the job to COMPLETED. After approval, use leave_review to rate the human. If the work needs changes, use request_revision instead.
    Connector
  • Get the training progress and metrics for a dataset version. Use this tool to check on a training job started with models_train. Returns training status, progress (current/total epochs), latest metrics (mAP, loss), and the URL to view training in the dashboard.
    Connector