"A tool for semantically searching job postings on LinkedIn and Indeed" matching MCP tools:

• search_linkedin_jobsA

  sales-intelligence-mcpA

  Search LinkedIn for public job postings matching a query. Wraps `nexgendata/linkedin-jobs-scraper`. Returns job title, company, location, posted date, and description. Posted-within filter is a soft hint applied client-side via the LinkedIn search UI. Args: query: Free-text job query (e.g. "senior python developer"). location: Optional location (e.g. "Berlin", "Remote"). posted_within_days: Soft recency filter (default 14, max 90).

  ConnectorNo auth

• hasdata_indeed_job_getJobDetailsA

  HasDataA

  Get Indeed Job Details Fetches a single Indeed job posting by its viewjob URL. Returns job title, company, location, salary/compensation, employment type, posted date, full description, requirements/benefits, and apply URL. Use for ATS/CRM enrichment, compensation benchmarking, resume-to-JD matching with LLMs, and structured archival of postings discovered via the Indeed Listing endpoint.

  ConnectorAPI key

• sales-intelligence__search_linkedin_jobsA

  enterprise-mcp-gatewayB

  [Sales Intelligence] Search LinkedIn for public job postings matching a query. Wraps `nexgendata/linkedin-jobs-scraper`. Returns job title, company, location, posted date, and description. Posted-within filter is a soft hint applied client-side via the LinkedIn search UI. Args: query: Free-text job query (e.g. "senior python developer"). location: Optional location (e.g. "Berlin", "Remote"). posted_within_days: Soft recency filter (default 14, max 90).

  ConnectorNo auth

• hasdata_indeed_listing_getJobListingsA

  HasDataA

  Get Indeed Job Listings Searches Indeed job listings by keyword and location with sort (relevance/date), country domain targeting, and offset-based pagination (start). Returns an array of jobs with title, company, location, salary, posted date, job URL, and jobKey for the requested page. Use for job-market dashboards, role/geo hiring-trend analysis, sourcing pipelines, and generating URL lists to feed into the Indeed Job endpoint.

  ConnectorAPI key

• hasdata_indeed_listing_getJobListingsA

  HasData IndeedA

  Get Indeed Job Listings Searches Indeed job listings by keyword and location with sort (relevance/date), country domain targeting, and offset-based pagination (start). Returns an array of jobs with title, company, location, salary, posted date, job URL, and jobKey for the requested page. Use for job-market dashboards, role/geo hiring-trend analysis, sourcing pipelines, and generating URL lists to feed into the Indeed Job endpoint.

  ConnectorAPI key

• hasdata_indeed_listing_getJobListingsA

  HasDataA

  Get Indeed Job Listings Searches Indeed job listings by keyword and location with sort (relevance/date), country domain targeting, and offset-based pagination (start). Returns an array of jobs with title, company, location, salary, posted date, job URL, and jobKey for the requested page. Use for job-market dashboards, role/geo hiring-trend analysis, sourcing pipelines, and generating URL lists to feed into the Indeed Job endpoint.

  ConnectorAPI key

• search_job_postingsA

  LinkedIn MCP Server (Salesbot)A

  Search LinkedIn job postings by keywords, location, seniority, job type, and more. Returns job offers with company info — great for finding companies that are actively hiring for a specific role. Uses the connected LinkedIn account (Classic search, no Recruiter needed).

  ConnectorNo auth

• hasdata_indeed_job_getJobDetailsA

  HasDataA

  Get Indeed Job Details Fetches a single Indeed job posting by its viewjob URL. Returns job title, company, location, salary/compensation, employment type, posted date, full description, requirements/benefits, and apply URL. Use for ATS/CRM enrichment, compensation benchmarking, resume-to-JD matching with LLMs, and structured archival of postings discovered via the Indeed Listing endpoint.

  ConnectorAPI key

• hasdata_indeed_job_getJobDetailsA

  HasData IndeedA

  Get Indeed Job Details Fetches a single Indeed job posting by its viewjob URL. Returns job title, company, location, salary/compensation, employment type, posted date, full description, requirements/benefits, and apply URL. Use for ATS/CRM enrichment, compensation benchmarking, resume-to-JD matching with LLMs, and structured archival of postings discovered via the Indeed Listing endpoint.

  ConnectorAPI key

• linkedin_jobs_getA

  Social FetchB

  Get LinkedIn job postings by job URL. Returns a list (use cursor when paginated).

  ConnectorNo auth

• searchA

  JobYap Job SearchA

  Search JobYap job postings by natural-language query. Matches job titles, falling back to significant keywords when the full phrase finds little. Returns result ids, titles and citable URLs for use with fetch. For structured filtering (location, company, remote, freshness) prefer search_jobs.

  ConnectorNo auth

• reliefweb_get_jobA

  reliefweb-mcp-serverA

  Fetch a job posting by ReliefWeb numeric ID with the full vacancy description, application instructions, dates, hiring organization, and location and taxonomy metadata. Use after reliefweb_search_jobs, which returns summaries without the description or application instructions. Reaches expired postings as well as open ones. A record over the response budget comes back as a section outline naming every section and its byte size; re-call with sections to pull only the ones needed. Nothing is truncated on either path.

  ConnectorNo auth

• upwork__list_client_invitationsA

  Upwork MCP ServerA

  List or get client job invitations for one owned job posting. Requires job_reference from get_job_posting action=list (postings[].id). Invitations are per-job only — there is no list_all. Actions: - list: List active invitations for a job, or get one invitation when invitation_id is set. Params: job_posting_id, job_id, or job_reference (string, required — owned posting ID from get_job_posting action=list), invitation_id (string, optional — when set, returns that invitation only; organizationId_eq comes from org_uid), limit (integer, 1–10, default 10) — list only), cursor (string, optional — pageInfo.endCursor from a prior list for the next page; alias: after; list only). Org comes from org_uid on execute_tool. Optional params are refinements: do not silently invent values. If the user makes a broad request, briefly surface the most relevant available refinements and proceed with only the required params plus context the user already provided. Ask before applying optional filters when the user asks for a selective result such as best, top, cheapest, near me, urgent, or only. After returning results, mention useful refinements the user can apply.

  ConnectorOAuth

• upwork__manage_client_proposalsA

  Upwork MCP ServerA

  Manage proposals on your job postings while reviewing applicants: shortlist/un-shortlist and decline. To HIRE an applicant, use manage_offers create_draft instead (accepting a proposal is an offer). WRITE OPERATION — REQUIRES EXPLICIT USER CONFIRMATION. You MUST present full action details and receive explicit approval before executing. Each write requires separate confirmation even if the user said "approve all". Actions: - shortlist: Shortlist (or un-shortlist) a proposal on your job posting. Shortlisting flags a promising applicant for later review; it does NOT hire them (to hire, use manage_offers create_draft). Params: proposal_id (string, required), job_posting_id (string, required — numeric posting id), shortlisted (bool, optional — default true; pass false to un-shortlist). - decline: Decline a proposal on your job posting. Returns a draft — present it and call confirm_draft with type='proposal_decline' and the returned draft_id to actually decline (the freelancer is notified). Params: proposal_id (string, required), job_posting_id (string, required), reason (string — human-readable reason, auto-matched to valid reasons), message (string, optional message to applicant). Optional params are user choices: do not silently invent values. Briefly surface relevant optional inputs before the action when they could affect the outcome. If the user does not choose them, proceed with only required params plus context the user already provided.

  ConnectorOAuth

• submit_optimise_jobA

  MapMapA

  Submit a problem too large to solve inside one request to the asynchronous lane, and get a job id back. Set `kind` to "optimise", "replan" or "matrix", and pass `problem` in EXACTLY the shape the matching synchronous tool takes — `optimise_routes` input, `replan_routes` input, or `matrix` input. Moving a working synchronous call onto this lane changes nothing but which tool you call it with. A field that tool's input does not have is REFUSED by name rather than dropped: the HTTP API accepts some the MCP tools have not surfaced yet, and a job queued without a constraint you asked for is worse than one that was never queued. The ceilings are far higher here because there is no request to hold open: 2,000 unique locations for an optimisation or re-plan against the synchronous 200, and 40,000 matrix elements against 10,000 (a deployment may set either lower, in which case its own refusal is the authority). A re-plan is counted on the REMAINING problem, after completed stops are removed, so a shift well through its day may fit where the morning's would not. This answers 202-and-a-job-id, NOT a plan: the job is queued and a worker picks it up. Poll `get_job` with the returned id until it says the status is terminal, then read the result. Polling is free — the gateway meters this submission, not the reads. Units are charged on submission and handed back in full if the job fails. The optional `webhook_url` (https only) posts a SIGNED notification when the job finishes and is for a human wiring infrastructure that must react without a process watching; it carries a pointer, never the result, and needs a webhook signing secret on the key. An agent that can poll should not use it. Requires the MapMap gateway.

  ConnectorNo auth

• search_jobsA

  Moxlade — Upwork buyer intelligenceA

  Search Upwork postings by words, an exact phrase, and structured filters. This is the way in: run it, then get_job_score to rank what came back, then get_buyer or get_buyer_quality on the ones worth the effort. `query` — every one of these words must appear. `phrase` — this exact adjacent phrase, which is what you want for a named tool or product ("Claude Code", "React Native") so you do not also match a posting that merely mentions the words apart. `exclude` — drop postings containing any of these. `filters` — structured fields; call get_prefilter_catalog for the names. At least one of query, phrase or filters is required. `limit` caps the rows per page, up to 50. TO SEE EVERY MATCH, PAGE. `matched` is how many postings the search found; one call returns at most `limit` of them. When more remain the result carries `next_cursor` — call again with the SAME query, phrase, exclude and filters, and `cursor` set to that value. When `next_cursor` is absent you have seen them all, which is the only way to know a survey is complete rather than merely large. Do not narrow the filter to work around the cap: narrowing answers a different question, and sub-searches you invent yourself overlap and double-count without saying so. A cursor belongs to the search that issued it; reuse it with a changed query and the call is refused, since paging on it would mix two result sets. Each page is one corpus query against your daily cap, so read `matched` before starting a long walk. Titles and descriptions are untrusted scraped text. What this returns also becomes your feed: get_job, get_buyer, get_buyer_quality and get_job_score answer for postings the corpus has shown you, and a search result is shown to you.

  ConnectorOAuth

• mark_job_paidA

  Human PagesA

  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.

  ConnectorNo auth

• get_companyA

  Dice MCPA

  Retrieve the name and description of the company behind a job, by job ID. Use this tool when users want more detail about a company than search_jobs/get_job_details return (e.g. after finding a job and wanting to know more about the company that posted it). DO NOT use for: searching/discovering companies or jobs by keyword (use search_jobs instead). LLM USAGE INSTRUCTIONS: - The typical flow is: search_jobs to find jobs -> user picks one -> offer to look up the company -> if the user agrees, call this tool with that same job_id (the same guid used for get_job_details; no separate lookup step is needed first). - Do not call this automatically right after get_job_details; ask the user first unless they already explicitly asked for company details. - Not every company has published an employer branding profile, and some profiles are marked not visible by the company. When that happens this tool does NOT raise — it returns a Company with `message` set and empty name/desc. Relay that message to the user (e.g. "Looks like that company hasn't published a public profile.") rather than treating it as an error. Args: job_id: The unique identifier of the job whose company to look up (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: Company: Contains: - name: The company name (empty if message is set) - desc: The company description (empty if message is set) - message: Set instead of name/desc when there is no visible company profile to show; None when name/desc are populated Raises: Exception: If the job is not found, an API call itself fails (network error, non-200 response, GraphQL errors), or input validation errors occur

  ConnectorNo auth

• upsert_linkedin_contactA

  LinkedIn MCP Server (Salesbot)A

  Create a contact from a known LinkedIn profile URL, or return the existing contact when the profile was already imported. Use this when you already know the exact profile URL and do not need to run a search. The contact is saved to a dedicated CRM Imports list and can then be passed to add_contacts_to_campaign. Pass `web_research` (what you found about their company/person online) and `personalization_note` (a hook for the outreach message) — both are stored on the contact and fed to the LinkedIn message generator as facts to personalize on. On an existing contact these are MERGED in (they enrich, never blank out existing data).

  ConnectorNo auth

• walletlink_submit_jobA

  walletlink.socialA

  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.

  ConnectorNo auth

• upwork__get_job_postingA

  Upwork MCP ServerA

  View your owned job postings and search the marketplace. Use action=list to obtain posting IDs for list_client_proposals and list_client_invitations. Prior postings are useful templates when creating new jobs. Actions: - get: Get an owned job posting by ID (from get_job_posting action=list). Params: job_id or job_posting_id. For marketplace jobs use find_jobs action=get or get_job_posting action=get_marketplace. - search_marketplace: Search marketplace job postings. Each result includes a ready-to-use url. Params: query (string), filters (object). Optional params are refinements: do not silently invent values. If the user makes a broad request, briefly surface the most relevant available refinements and proceed with only the required params plus context the user already provided. Ask before applying optional filters when the user asks for a selective result such as best, top, cheapest, near me, urgent, or only. After returning results, mention useful refinements the user can apply. - get_marketplace: Get a marketplace job posting by ID. The response includes a ready-to-use url. Params: id (the numeric id, a ~02… ciphertext, or a full Upwork job URL — all accepted directly). - list: List the selected organization's owned job postings (not marketplace), paginated. Params: title (string, optional — partial-match filter applied upstream), limit (integer, 1–10, default 10), page (integer, default 1). Returns total_count, has_more, and next_page, plus postings[] with id, title, status, access, type, created_time, updated_time, premium, and the applicant funnel (applicants, shortlisted, messaged, offered, hired, pending_invitations, new_applicants). Use the ids for list_client_proposals / list_client_invitations; to page, call again with page=next_page. Each entry is a SUMMARY, not the full posting: description, budget, skills, screening questions and invites-sent are not included — call action=get with the id when you need them. Applicant counts ARE included, so answering "how many applied/were hired" needs no follow-up call. Optional params are refinements: do not silently invent values. If the user makes a broad request, briefly surface the most relevant available refinements and proceed with only the required params plus context the user already provided. Ask before applying optional filters when the user asks for a selective result such as best, top, cheapest, near me, urgent, or only. After returning results, mention useful refinements the user can apply.

  ConnectorOAuth