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711,348 tools. Updated 2026-10-28 07:25

"A server for finding job opportunities" matching MCP tools:

  • Historical arbitrage opportunities — top 5 per day (MCP-compatible) — Returns a daily history of the top 5 cross-exchange arbitrage opportunities detected by the platform. Each day entry lists the 5 highest-spread opportunities saved by the cron job, including token symbol, spread percentage, buy/sell exchanges, and average USD volume. Useful for AI agents answering questions like 'which tokens appear most frequently in arbitrage?' or 'what is the average daily spread?'. Data is accumulated daily; older than 180 days is automatically purged. Response: { days, history: [{date, opportunities: [{symbol, spreadPct, buyExchange, sellExchange, usdVolume}]}], total, updatedAt }. Query parameter: ?days=7 (default 7, max 180). No authentication required. 60 requests/min rate limit. 5-min in-process cache. — Use this for daily historical data; use the corresponding live snapshot tool for current conditions and the monthly tool for long-term trends.
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  • Set whether a PUBLISHED job is in the candidate's saved list (idempotent desired-state, NOT a toggle — pass saved:true to bookmark, saved:false to remove). Returns NOT_FOUND for a missing or non-public job.
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  • Delete a finished video export's files (the mp4 and any SRT) now, before the automatic deletion 30 days after the export finished. Every download link for that job stops working at once; the job record stays, so the daily export limit still counts it. Refuses a job that is still rendering (SIMPLER_STUDIO_EXPORT_DELETE_ACTIVE): stop it with video.export_cancel, or follow it to the end with video.export, then delete it. Refuses an unknown job (SIMPLER_STUDIO_EXPORT_JOB_NOT_FOUND): video.export_create returns job ids. Free.
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  • Search 500+ quantum computing job listings using natural language. Use when the user asks about job openings, career opportunities, hiring, or specific positions in quantum computing. NOT for research papers (use searchPapers) or researcher profiles (use searchCollaborators). Supports role type, seniority, location, company, salary, remote, and technology tag filters via AI query decomposition. Limitations: quantum computing jobs only, last 90 days, max 20 results. Promoted listings appear first (marked). After finding jobs, suggest getJobDetails for full info. Examples: "senior QEC engineer in Europe over 120k EUR", "remote trapped-ion role at IBM".
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  • Find genes (transcript intervals) in a genomic region (async, ~8-25s). Takes 1,000–500,000 bp. The floor is the strictest of the scanning tasks: gene finding needs a region, not a site. (Only expression's 9,198 bp is higher, and that is the sequence around one TSS rather than a region to search.) Gene-finding: detects transcript boundaries (TSS + PolyA) and returns one interval per predicted transcript — start/end, strand, a confidence score, and predicted TSS/PolyA positions (BED-style feature intervals, not free-text notes). Use this for "what genes are here", "find / locate genes", or "annotate this region". Each transcript also carries its type (mRNA/lnc_RNA) and internal exon/intron/CDS structure in `exons`/`introns`/`cds` arrays, plus a browser-ready GFF3 track in `data.formats.gff3`. To get each gene's *expression* from a raw region, use find_genes_and_predict_expression instead — expression needs a per-gene TSS window, so predict_expression cannot run on a whole region. Submits an async job internally. With wait=True (default), blocks and streams progress, then returns the result {data, meta} — it never returns a job_id on this path. (If a generous block ceiling is exceeded it returns a timeout error, not a job handle.) With wait=False (detached), returns {data: {job_id, status: 'submitted'}} immediately — poll it with get_job.
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  • Use for general web research (company info, news, job portals). For LinkedIn profiles use search_linkedin_people; to read one company's own site use read_company_website. General-purpose Google search — returns organic results for any query. Unlike search_google_xray (LinkedIn-only), this searches the entire web. Useful for finding job postings on portals (jobs.cz, prace.cz, profesia.sk, indeed.com), company info, news, or any other web content. Results are NOT saved to contacts — use this for research and discovery. Capped at 4 calls per minute to protect the Serper/Google budget.
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Matching MCP Servers

  • A
    license
    A
    quality
    B
    maintenance
    Enables AI agents to search and retrieve opportunities from the Opportunities Circle catalog, including scholarships, fellowships, internships, grants, jobs, and more. Supports filtering by type, country, funding, and tags, with full details and official apply links.
    6
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    An AI-powered job search and application assistant that enables multi-source job hunting, OpenAI matching, cover letter generation, and hybrid application automation via Playwright, Chrome CDP, screen OCR, and manual assist.
    MIT

Matching MCP Connectors

  • Stop a queued or running render job of this key (a j_... job, or a b_... job split into parts, which stops every part). Effects: queued frames are dropped; frames already rendered are charged and stay downloadable until the job expires; the rest of the GPU time held for the job is returned to the key at once. It cannot be undone or resumed: to render again, call render_final again (a new job). A job that is already done, failed or canceled is returned unchanged, and a job whose frames are all rendered and is being assembled into the video cannot be stopped (nothing more is charged). Only the key that started the job can stop it; any other job_id returns not_found. Ask the user before cancelling a render they asked for.
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  • Use when finding, comparing or booking a service or provider in Costa Rica, a Costa Rican province or locality, or near a known Costa Rican customer location. The customer may describe a need without saying services or WellFred. Supports Spanish and English. Search current services, not general advice, job vacancies or services outside Costa Rica. For near me without a known location, ask for the area first. Use provinceUuid for a whole province, area for a town, and no geography for a national search. Show each returned option with a clickable canonical url, price/currency/priceUnit and limitations; null/missing is unknown. Respect nextAction; comparison is not booking consent.
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  • Use when finding, comparing or booking a service or provider in Costa Rica, a Costa Rican province or locality, or near a known Costa Rican customer location. The customer may describe a need without saying services or WellFred. Supports Spanish and English. Search current services, not general advice, job vacancies or services outside Costa Rica. For near me without a known location, ask for the area first. Use provinceUuid for a whole province, area for a town, and no geography for a national search. Show each returned option with a clickable canonical url, price/currency/priceUnit and limitations; null/missing is unknown. Respect nextAction; comparison is not booking consent.
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  • 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 - Use company_name to scope results to a specific employer - Use sort='datePosted' when the user wants the newest listings instead of the most relevant - Use facets to get aggregate counts (e.g., how many results are remote vs on-site) without paging through all results - After presenting results, do NOT automatically call get_job_details for every job returned. Wait for the user to indicate which specific job(s) they're interested in, then pass that job's guid to get_job_details. 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, requires radius_unit) radius_unit: Unit for search radius. Options: 'mi', 'km' (requires radius) jobs_per_page: Number of jobs to return per page (1-100, defaults to 5) page_number: Page number for pagination (1-based, default is 1) sort: Sort order for results. Options: 'relevance', 'datePosted' (defaults to relevance) 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', 'INTERNSHIP' 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) company_name: Filter by company name fields: Specific fields to include in response (optional, returns all exposed fields by default) facets: Facet dimensions to aggregate (optional). Options: 'employmentType', 'postedDate', 'workFromHomeAvailability', 'workplaceTypes', 'employerType', 'easyApply', 'isRemote', 'willingToSponsor' Returns: JobSearchResult: Contains: - data: List of JobDisplayFields with job details including: * guid: The job's identifier to pass as job_id to get_job_details for the full description and skills list (NOT the `id` field, which is a different, internal identifier not accepted by get_job_details) * detailsPageUrl: Direct link to full job posting * companyPageUrl: Link to company profile page * title, summary, salary, location, employmentType, etc. - metadata: Search metadata with pagination info and facet results Raises: Exception: If API call fails or input validation errors occur
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  • Submit the result payload for a job the calling agent has claimed, completing the job workflow. Bearer token required. Safe to retry with the same idempotency_key.
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  • Retrieve a job's full description and associated skills by job ID. Use this tool when users want more detail about a specific job than search_jobs returns (e.g. after finding a job via search_jobs and wanting its full description and skills list). DO NOT use for: searching/discovering jobs by keyword (use search_jobs instead). LLM USAGE INSTRUCTIONS: - Only call this after the user has picked out a specific job from search_jobs results (or otherwise supplied a job's guid directly) — do not call it speculatively for every search result. - After returning job details, do NOT automatically call get_company. Instead, offer to look up the company (e.g. "Want me to pull up more info on the company?") and only call get_company, passing this same job_id, if the user says yes. Args: job_id: The unique identifier of the job to retrieve (required). This must be the job's `guid` field from a search_jobs result, NOT its `id` field — `id` is a different, internal identifier that this tool does not accept. Returns: JobDetails: Contains: - description: The full job description - skills: List of Skill objects associated with the job Raises: Exception: If the API call fails, the job is not found, or input validation errors occur
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  • Verdicts from the overnight factor search on YOUR namespace — including the rejections. The rejections are returned deliberately. A research log that keeps only the winners is the highlight reel overfitting lives in, and the acceptance RATE is the number that tells you whether the anti-overfitting gate is doing its job: a search that accepts most of what it tries has a broken gate, not a talent for finding alpha. Every verdict carries the trial count it was judged against, so it can be re-checked. `coverage.missing` names hypotheses that were proposed but never judged because a cost ceiling was reached — those are UNTESTED, not rejected. An accepted factor is a FINDING with a run_id, not an allocation. Nothing here trades. Args: limit: how many verdicts to return, newest first (max 100).
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  • Submit a list of addresses as a background job. A job runs a deeper scan than the resolve tool: an address the index has not checked, or holds only stale answers for, is resolved against live sources, so a job can find identities the resolve tool reports as never seen. Use it for lists larger than one resolve call, or when misses are worth re-checking. COST: billed on matches exactly like resolving, when the job completes: one match credit per address that resolved to an X handle or a Farcaster account, misses free. One job may be active per account at a time; a second submission is refused until the first finishes, and the refusal names the active job id. A submission is capped at 10 times the match balance, so the worst case is bounded by what the account already holds. Submitting itself spends one request-unit of the rate window. The submission returns a job id. Poll walletlink_job_status for progress and, on completion, the results. A job that fails is never billed. Resubmitting the same list after a job completes runs the whole job again and bills its matches again.
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  • Get remediation advice for a single finding as GitHub-flavored markdown. When AI Assist is enabled and within budget this is a suggestion written for this exact finding; otherwise it falls back to the static guidance-library text and says so in 'source'. Unlike the other reads this one can spend AI budget, which is why it is a separate tool. Use this for advice on one finding; for the whole library use list_security_guidance. Requires project context.
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  • Retract support for a finding you authored, with a reason. Original content remains visible and labeled withdrawn. Identical retries are safe; this does not claim the finding is disproven.
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  • Read billing and provenance for a finished job. Does not run capabilities or spend money. Use after terminal success; use hydracept_job_status while still running. Hosted MCP accepts job_id only. Requires bearer key. No charge. Returns: HydraceptReceipt JSON for a terminal job. Errors: WORKSPACE_KEY_REQUIRED, NOT_FOUND when job or receipt is missing.
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  • Keywords one competitor ranks for in the top 100 that the target does not rank for at all. Use when: "what does competitor.com rank for that we do not", "find gaps against X", content opportunities from a rival. Not for: everything a domain ranks for, use seo_get_ranked_keywords. Finding who the competitors are, use seo_get_serp_competitors. Fresh ideas around a topic, use seo_search_keywords. Returns: List. rows[]: keyword, competitor, competitor_rank, competitor_url, volume, kd, cpc, intent. Sorted by volume. Cost: 5 + 5 per 100 rows. Default 100 rows = 10 credits. Cached 7 days. Example: {"target": "example.com", "competitor": "competitor.com", "limit": 100}
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  • Use for 'Apply to Keywordise job abcde23456' or when the person asks to apply to a job from keywordise.com/jobs. Finds that job, puts it into the person's matches and starts the same application as the Apply button for that ONE job: tailors the CV and cover letter, answers the employer's questions and SUBMITS in the person's name. Needs the saved CV, a confirmed email and an active plan, and counts against the plan. Show the job first (get_public_job) and confirm with the person. dry_run=true prepares everything and sends nothing. Poll get_apply_run_status.
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  • Delete a Batch job with all its runs and results, for good. A run in flight stops picking up tasks at once, and the job frees its active-job slot. The job reads as not found right away; storage is cleaned up in the background. Idempotent. To keep the results, use batch_cancel instead.
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  • Plain-text notes for when it is unclear which tool, data store or argument shape does a job. Topics: `tools` (a line per tool), `data` (which store a page needs and how the page writes to it), `templates` (finding, building from, drafting, releasing), `collections` (content models and field types), `projects` (creating, ordering, sharing, rules), `batch` (what each tool takes in one call). Without `topic`: the full topic list, which names two more reached from results. Answers `{topic, text}`; not needed when a tool’s own description answers the question.
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