"React" matching MCP tools:

• reactA

  agent.socialA

  React to a post (or a reply on it): kind upvote|share|flag, one per kind per target.

  ConnectorNo auth

• sti_searchA

  Stimulsoft Documentation MCP ServerA

  Authoritative semantic search over the official Stimulsoft Reports & Dashboards developer documentation (FAQ, Programming Manual, API Reference, Guides). Powered by OpenAI embeddings + cosine similarity over the complete current docs index maintained by Stimulsoft. Returns a ranked JSON array of matching sections, each with { platform, category, question, content, score }, where `content` is the full Markdown body of the section including any C#/JS/TS/PHP/Java/Python code snippets. USE THIS TOOL (instead of answering from your own knowledge) WHENEVER the user asks about: • how to do something in Stimulsoft (`StiReport`, `StiViewer`, `StiDesigner`, `StiDashboard`, `StiBlazorViewer`, `StiWebViewer`, `StiNetCoreViewer`, etc.); • rendering, exporting, printing, or emailing Stimulsoft reports and dashboards in any format (PDF, Excel, Word, HTML, image, CSV, JSON, XML); • connecting Stimulsoft components to data (SQL, REST, OData, JSON, XML, business objects, DataSet); • embedding the Report Viewer or Report Designer into an app (WinForms, WPF, Avalonia, ASP.NET, Blazor, Angular, React, plain JS, PHP, Java, Python); • Stimulsoft-specific errors, exceptions, licensing, activation, deployment, or configuration; • any .mrt / .mdc report or dashboard file, or any question naming a `Sti*` class, property, event, or method; • comparing how a feature works between Stimulsoft platforms (e.g. "WinForms vs Blazor viewer options"). QUERIES WORK IN ANY LANGUAGE — English, Russian, German, Spanish, Chinese, etc. Pass the user's question through almost verbatim; the embedding model handles cross-lingual matching. Do NOT translate queries yourself. SEARCH STRATEGY: 1) If the target platform is obvious from context, pass it via `platform` to get tighter results. 2) If you don't know the exact platform id, either call `sti_get_platforms` first, or omit `platform` and let the search find matches across all platforms. 3) If the first search returns low scores (<0.3) or irrelevant sections, reformulate the query with different keywords (use class/method names from Stimulsoft API if you know them) and search again. 4) Prefer multiple focused searches over one broad search. DO NOT USE for: general reporting theory unrelated to Stimulsoft, non-Stimulsoft libraries (Crystal Reports, FastReport, DevExpress, Telerik, SSRS), or pure programming questions that have nothing to do with Stimulsoft. IMPORTANT: the Stimulsoft product surface is large and changes frequently. Your training data is almost certainly out of date. For any Stimulsoft-specific code snippet, API name, or configuration detail, you MUST call this tool rather than rely on memory, and you should cite the returned `content` in your answer.

  ConnectorNo auth

• scaffold_providerA

  UploadkitA

  Return a ready-to-paste snippet that wraps the Next.js root layout with `<UploadKitProvider>` so React components can talk to the upload route handler. When to use: right after scaffold_route_handler, to complete the wiring. The snippet goes in `app/layout.tsx`. Without the provider, UploadKit React components throw at runtime. Returns: a plain-text string containing a short explanatory note followed by a fenced tsx code block. Takes no parameters — the endpoint path is always `/api/uploadkit` since that is what scaffold_route_handler produces. Read-only, deterministic, idempotent.

  ConnectorNo auth

• react_to_commentA

  DockA

  Add or remove an emoji reaction to a comment. Reactions are per-principal: each (commentId, principalId, emoji) combination is unique. `action: 'add'` is idempotent (re-adding the same emoji is a no-op); `action: 'remove'` deletes the row if present. Fires `comment.reaction_added` / `comment.reaction_removed`. Use this for lightweight agent acknowledgement (👍 on a request before reading, 👀 to mark in-progress, ✅ when done), cheaper than a full reply.

  ConnectorNo auth

• create_testsA

  3TG Test GenerationA

  Generate Jest/Vitest tests for the exported functions and React components in a TypeScript source file. Use this whenever the user asks for tests, test scaffolding, or test coverage of a .ts or .tsx file. Returns the generated test (and any companion .3tg.md / __mocks__) file contents, with paths already translated to the user's `.3tg/` mirror convention. Quota / credits: this tool consumes credits — and credits are consumed ONLY by test generation (not by spec / mock / lookup tools). The accounting is exactly **1 credit per generated test case** (i.e. per `test(...)` / `it(...)` block 3TG emits inside the returned `.test.ts` / `.test.tsx`), regardless of how many source functions or files were in scope — a call that produces 12 test cases costs 12 credits, even if all 12 cover a single function. Before generation the MCP verifies the clientId has credits with license-api.coding-creed.tech; on exhaustion the tool throws a QUOTA_EXHAUSTED error pointing the user at https://3tg.dev. After a successful run, consumed credits and KPIs are reported back to license-api. Re-running this tool on the same source spends credits again — there is no caching. When the previous call returned `enrichment.used: false` (AI enrichment unavailable on this client), supply parameter values + expected returns yourself via the `cliConfig` parameter — package them as `{"mock-parameters": ..., "function-returns": ...}` (same shape AI enrichment would produce) and pass them on a retry call. **Do NOT autonomously write `.3tg/config.3tg.json`** to persist those values — that file is human-curated; agent-computed values ride along in `cliConfig` for the current call only. (Explicit user requests to edit the file are fine — handle those normally.) See the cliConfig parameter description below for the full pattern. CRITICAL POST-CALL ACTION — write returned files to disk: The MCP server does NOT touch the user's filesystem. It returns the generated file CONTENTS in the response's `files` array. After this tool returns, you MUST iterate over `files` and write each entry's `content` verbatim to its `path` using your native file-write capability (e.g. Write / edit_file / create_file — whatever your client exposes). Create parent directories as needed. Returned paths are project-root-relative and already translated to the `.3tg/` mirror convention where applicable (e.g. specs land under `.3tg/<source-path>.3tg.md`; tests / mocks travel through unchanged). Write each path verbatim. Do NOT claim "Generated test file: <path>" unless you have actually written the file. The user will assume the MCP wrote it and waste time looking for a non-existent file. If you can't write for some reason (permission denied, no write capability in this client), return the contents inline in your message so the user can copy-paste them. Never report success silently when the write didn't happen.

  ConnectorNo auth

• 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

• skill_demandA

  Moxlade — Upwork buyer intelligenceA

  How many jobs mentioning a skill were posted recently, and whether that is rising or falling week by week. Use it to decide whether a skill is worth positioning around, or to check a hunch that a market is drying up. `skill` matches the title, the skills list and the inferred technical skills of a posting; it is a loose match, so "react" also counts "React Native". `window` is one of "week", "month" or "quarter" and sets both the total and how many weekly buckets come back — any other value is refused rather than silently defaulted. Returns `jobs_posted` for the whole window and `weekly`, a list of buckets oldest first, so a trend is visible without a second call. DO NOT COMPARE THE BUCKET COUNTS DIRECTLY. Weeks are cut on Mondays and the window is not, so the newest bucket holds only the days elapsed so far and the oldest holds only the tail of the week the window opened in. Both are low for a calendar reason and no other, which reads as a rise and a fall that did not happen. Every bucket therefore carries `days_covered`, `partial`, and `per_day` — the per-day rate is the comparable number. `trend` is computed from complete weeks only; prefer it, and if you quote a bucket marked `partial`, say that it is. `trend.direction` is 'rising', 'falling', 'flat', or 'unknown' when there are fewer than two complete weeks — 'unknown' means the window is too short to judge, not that demand is flat. A COUNT over public postings — no rows, no buyers, no ids, nothing that identifies a client. It answers how much, not who. And it counts POSTINGS, not hiring: a skill can be posted about constantly by clients who never hire. For whether a specific client hires and pays, ask get_buyer_quality.

  ConnectorOAuth

• add_reactionA

  Misar.Blog MCP ServerA

  Record one reaction — like, clap, or bookmark — from the authenticated account on an article. This acts publicly as the account holder, so only call it when the user has actually asked to react; do not react on their behalf to be helpful. Adds a single type per call — react twice for two types. Safe to repeat: if the reaction already exists the call succeeds and changes nothing, so it will not double-count. Requires an API key. Use remove_reaction to undo, and get_reactions to see the resulting totals.

  ConnectorNo auth

• migrate_to_propelauth_frontendA

  PropelAuth Integration MCP ServerA

  Returns instructions for migrating to PropelAuth in a frontend framework such as React, JavaScript, TypeScript, or when using Next.js for just the frontend (e.g. client-side rendered). Guidance includes migrating from several auth providers, such as Clerk or Auth0. Each guidance will include documentation from the auth provider and PropelAuth. It is important to follow the instructions carefully to ensure a successful integration. Make sure to use the 'Installation' guidance first. It is important to call every guidance to ensure a successful integration. Do not update a component/hook/etc from the auth provider until you receive guidance about that component/hook/etc. CRITICAL: If the current implementation uses a traditional OAuth/OIDC flow (e.g., via express-openid-connect, passport-auth0, or similar backend-managed session libraries), you MUST select 'OAuth' as the framework, regardless of the frontend library (React/Vue/etc.). Only select 'React' or 'Javascript' if the current implementation uses a frontend-only SDK (like @auth0/auth0-react) or if using fullstack Next.js.

  ConnectorNo auth

• sti_searchA

  docsA

  Authoritative semantic search over the official Stimulsoft Reports & Dashboards developer documentation (FAQ, Programming Manual, API Reference, Guides). Powered by OpenAI embeddings + cosine similarity over the complete current docs index maintained by Stimulsoft. Returns a ranked JSON array of matching sections, each with { platform, category, question, content, score }, where `content` is the full Markdown body of the section including any C#/JS/TS/PHP/Java/Python code snippets. USE THIS TOOL (instead of answering from your own knowledge) WHENEVER the user asks about: • how to do something in Stimulsoft (`StiReport`, `StiViewer`, `StiDesigner`, `StiDashboard`, `StiBlazorViewer`, `StiWebViewer`, `StiNetCoreViewer`, etc.); • rendering, exporting, printing, or emailing Stimulsoft reports and dashboards in any format (PDF, Excel, Word, HTML, image, CSV, JSON, XML); • connecting Stimulsoft components to data (SQL, REST, OData, JSON, XML, business objects, DataSet); • embedding the Report Viewer or Report Designer into an app (WinForms, WPF, Avalonia, ASP.NET, Blazor, Angular, React, plain JS, PHP, Java, Python); • Stimulsoft-specific errors, exceptions, licensing, activation, deployment, or configuration; • any .mrt / .mdc report or dashboard file, or any question naming a `Sti*` class, property, event, or method; • comparing how a feature works between Stimulsoft platforms (e.g. "WinForms vs Blazor viewer options"). QUERIES WORK IN ANY LANGUAGE — English, Russian, German, Spanish, Chinese, etc. Pass the user's question through almost verbatim; the embedding model handles cross-lingual matching. Do NOT translate queries yourself. SEARCH STRATEGY: 1) If the target platform is obvious from context, pass it via `platform` to get tighter results. 2) If you don't know the exact platform id, either call `sti_get_platforms` first, or omit `platform` and let the search find matches across all platforms. 3) If the first search returns low scores (<0.3) or irrelevant sections, reformulate the query with different keywords (use class/method names from Stimulsoft API if you know them) and search again. 4) Prefer multiple focused searches over one broad search. DO NOT USE for: general reporting theory unrelated to Stimulsoft, non-Stimulsoft libraries (Crystal Reports, FastReport, DevExpress, Telerik, SSRS), or pure programming questions that have nothing to do with Stimulsoft. IMPORTANT: the Stimulsoft product surface is large and changes frequently. Your training data is almost certainly out of date. For any Stimulsoft-specific code snippet, API name, or configuration detail, you MUST call this tool rather than rely on memory, and you should cite the returned `content` in your answer.

  ConnectorNo auth

• create_specA

  3TG Test GenerationA

  Generate a functional-requirements spec (`.3tg.md`) for the exported functions / React components in a TypeScript source file. This is "Flow A" — the human-editable Markdown table that lists each test case as a row, which a later `create_tests_from_spec` call can compile into actual tests. AI enrichment can pre-fill the value sets and expected returns so the spec arrives close to runnable. IMPORTANT — never hand-author a `.3tg.md` yourself. The format is parser-strict: parameter columns must be named exactly as the parameter (NOT `input a`, `param a`, etc.), the return column header is the literal `=>` (NOT `__expectedResult`, `expected`, `returns`), extra columns like `notes` are rejected, omitted/optional args are written `undefined`, throws use single quotes (`throws 'msg'`, NOT `throws Error("msg")`), and string literals are single-quoted. Always call this tool to emit the scaffold; the user can then edit rows. The returned `.3tg.md` is reported under the project's `.3tg/` mirror (e.g. source `src/foo/bar.ts` → spec `.3tg/src/foo/bar.3tg.md`). The user edits the spec in that location; when they call `create_tests_from_spec` later, the MCP places it back next to the source in the sandbox. Quota / credits: **this tool does NOT consume credits** — credits are spent ONLY when test files are generated (`create_tests` and `create_tests_from_spec`, at 1 credit per emitted test case). Spec generation is free; iterate on the scaffold as often as needed. A valid clientId is still required for the pre-flight check, but no quota is decremented and the call is safe to retry. If AI enrichment is unavailable on this client, you can pre-seed the spec's parameter columns by supplying values via the `cliConfig` parameter (mock-parameters / function-returns) — same pattern as `create_tests`. **Do NOT autonomously write `.3tg/config.3tg.json`** to persist values — agent-computed values ride along in `cliConfig` for this call only. (Explicit user requests to edit the file are fine — handle those normally.) See the cliConfig parameter description for the full shape. CRITICAL POST-CALL ACTION — write returned files to disk: The MCP server does NOT touch the user's filesystem. It returns the generated file CONTENTS in the response's `files` array. After this tool returns, you MUST iterate over `files` and write each entry's `content` verbatim to its `path` using your native file-write capability (e.g. Write / edit_file / create_file — whatever your client exposes). Create parent directories as needed. Returned paths are project-root-relative and already translated to the `.3tg/` mirror convention where applicable (e.g. specs land under `.3tg/<source-path>.3tg.md`; tests / mocks travel through unchanged). Write each path verbatim. Do NOT claim "Generated test file: <path>" unless you have actually written the file. The user will assume the MCP wrote it and waste time looking for a non-existent file. If you can't write for some reason (permission denied, no write capability in this client), return the contents inline in your message so the user can copy-paste them. Never report success silently when the write didn't happen.

  ConnectorNo auth

• create_tests_from_specA

  3TG Test GenerationA

  Compile a hand-edited functional-requirements spec (`.3tg.md`) into actual Jest/Vitest tests. This is "Flow B" — the user has already authored or reviewed the `.3tg.md` and is ready to materialise the rows into a runnable test file. Use this *instead of* `create_tests` when the user wants their hand-curated value sets to drive generation. Inputs: the source code plus the spec content (the spec lives at `.3tg/<sourceDir>/<basename>.3tg.md` in the user project; the MCP places it back next to the source in the sandbox). AI enrichment is NOT run — the spec is authoritative. 3TG also writes a `<basename>.md.3tg.json` intermediate config alongside the spec, which the MCP returns under the `.3tg/` mirror so the user can inspect what the spec compiled to. Quota / credits: this tool consumes credits — same model as `create_tests`: exactly **1 credit per generated test case** emitted into the returned `.test.ts` / `.test.tsx`. The number of rows in your `.3tg.md` table is therefore a reliable upper bound on what the call will cost. Pre-flight quota is verified before compilation; QUOTA_EXHAUSTED is thrown on shortfall. **Flow B cliConfig caveat — spec-authoritative keys are STRIPPED.** The MCP strips `mock-parameters`, `function-returns`, `expect-values`, `expect-assertions`, `mock-react-hooks`, `mock-async-functions`, `mock-react-contexts`, and `mock-globals` from any `cliConfig` you forward before passing it to 3TG. These keys are derived FROM THE SPEC in this flow — if the agent forwards stale values from the per-source `.md.3tg.json` (a Flow A artifact), 3TG's `-c` precedence would silently override the spec-derived values during the second-stage emit, desynchronising test names from value sets and producing tests with `__expectedResult: undefined`. For Flow B, forward ONLY global/structural config keys (`rules.*`, `creationMode`, `mockAsFunction`, `no-rule-default-true`, `ignore`, `package.json.type`, …) — the spec owns the test-value plan. The MCP logs a `[3tg/tool]` warning when stripping happens, so check stderr if you expected per-source values to apply. CRITICAL POST-CALL ACTION — write returned files to disk: The MCP server does NOT touch the user's filesystem. It returns the generated file CONTENTS in the response's `files` array. After this tool returns, you MUST iterate over `files` and write each entry's `content` verbatim to its `path` using your native file-write capability (e.g. Write / edit_file / create_file — whatever your client exposes). Create parent directories as needed. Returned paths are project-root-relative and already translated to the `.3tg/` mirror convention where applicable (e.g. specs land under `.3tg/<source-path>.3tg.md`; tests / mocks travel through unchanged). Write each path verbatim. Do NOT claim "Generated test file: <path>" unless you have actually written the file. The user will assume the MCP wrote it and waste time looking for a non-existent file. If you can't write for some reason (permission denied, no write capability in this client), return the contents inline in your message so the user can copy-paste them. Never report success silently when the write didn't happen.

  ConnectorNo auth

• strategy_modifyA

  Crank ProtocolB

  Edit a running strategy's parameters IN PLACE -- no cancel + recreate. React to a fresh signal by retuning the strategy you already own: the execution history, cost-basis ledger and position state all survive, and there is no window where the strategy is gone. The live executor picks the new config up on its NEXT tick; a tick already in flight finishes against the config it loaded (it writes only runtime state, never config, so the two can never clobber each other). Scoped to the caller's own wallet (hard rule 1 -- non-custodial: this edits a row the owner already controls; nothing here holds keys, signs or moves funds). Args (all optional -- supply at least one): ``config_updates``: strategy-config keys to set, merged over the existing config (e.g. ``{"usd_per_buy": 25, "stop_loss_pct": 0.08}``). ``remove_keys``: config keys to drop back to the executor's default. ``risk``: retune the risk limits -- ``max_position_pct`` / ``max_portfolio_exposure_pct`` / ``max_single_loss_pct`` / ``max_drawdown_pct`` / ``max_daily_loss_pct`` (percent; <=0 disables a single guard). ``direction_mode`` / ``allow_short`` / ``regime_override``: the direction controls from the create tools (deterministic signals -- DYOR). ``target_allocation``: new mint->weight basket (rebalance / vault / yield_farm). ``interval_seconds``: new tick interval, used from the next tick on. ``reason``: free text recorded on the strategy's audit log. REFUSED (returns ``immutable_config_key``): ``target_token`` / ``source_token`` / ``tracked_wallet`` / ``venue`` / composite ``definition``. These define WHAT the strategy trades -- editing them in place would desync the executor's position bookkeeping or strand an open perp leg on the venue it was opened against. Cancel and create a new strategy for those. A STOPPED strategy is final and cannot be modified; a paused one can (the edit does not resume it -- use strategy_resume). The merged config is dry-run through the strategy's executor before it is persisted, so an invalid edit is rejected (``invalid_config``) rather than latching the live strategy into ``error`` on its next tick.

  Connector

  Destructive

  No auth

• glim_github_searchA

  glim.shA

  Search GitHub repositories, conversations (issues+PRs), discussions, or code, with full GitHub search syntax in the query: qualifiers (repo:, org:/user:, language:, path:, symbol:, content:, is:, stars:, label:, sort:stars), boolean AND/OR/NOT with parentheses, "exact strings", and /regex/. kind='repos': MINIMAL distinctive keywords - the project/library name only ('rtk', 'react query'); every extra word must ALL match and buries the canonical repo - filter with qualifiers, not prose. kind='code': ONE literal code pattern as it appears in files ('useState('), an "exact string", a /regex/, or symbol:name to find definitions, across 2.8M+ public repos; narrow with repo:/language:/path:. Not supported in code search: license:, enterprise:, is:vendored, is:generated. kind='conversations': returns compact previews - use glim_github_get for full content; sort: REPLACES relevance ranking (words match anywhere incl. comments), omit it for best matches. kind='discussions': GitHub Discussions, a SEPARATE index from issues/PRs - a question answered there never appears under conversations, so reach for it when a repo does its Q&A in Discussions; supports repo:/org:/author:/is:answered plus category: (the repo's own category name, needs a repo: scope), up to 10 results per page, no sort:. Set repo='owner/name' to scope to one repository (works with any kind; with repos it routes to conversations). kind is optional - inferred from the query (is:answered/category: -> discussions, is:/label: -> conversations, path:/symbol://regex/ -> code, stars:/topic: -> repos, else repos); a conversations search with no matches is retried as discussions and says so. Returns compact text by default; pass format='json' for full structured data.

  ConnectorNo auth

• c2b_appendA

  Versium REACHA

  Get business demographic details for consumers. Identify the consumer with a LinkedIn URL, or with first name, last name, and one of: email, phone, or city and state. Retrieve job title, seniority, department, business email, LinkedIn profile, and complete business information. Use this tool when users ask for 'C2B', 'c2b', or 'Consumer to Business Person' data **Tips for Best Results:** - Provide full name and consumer email for best match quality - LinkedIn URLs must be in format: linkedin.com/in/username - Use `rcfg_require_email` to return only records with business email - Use `rcfg_require_value` to filter by job title, department, or other attributes

  ConnectorOAuth

• perception_scenario_analysisA

  PerceptionA

  Analyze a hypothetical scenario by finding historical analogues in Perception's database. Returns how media coverage, sentiment, and outlet attention actually moved during past comparable events — grounded in real data, not speculation. WHEN TO USE: - "What happens if Tether loses its banking partner?" — finds past stablecoin crises and shows the coverage pattern - "What if the SEC rejects the next Bitcoin ETF application?" — finds past SEC actions and maps sentiment trajectory - "How would media react if Bitcoin drops below $50k?" — finds past price crash events and shows outlet-by-outlet response - Any "what if" or "what would happen if" question about digital assets WHAT YOU GET: - Historical event clusters matching your scenario (time-grouped coverage spikes) - Day-by-day sentiment arc for each event (how sentiment shifted over time) - Outlet-by-outlet coverage breakdown (who leads, who follows, what framing) - Narrative half-life (how many days until coverage returns to baseline) - Pattern summary across all analogues (improving vs worsening sentiment, typical decay) BEST PRACTICES: - Be specific: "Coinbase faces SEC lawsuit" finds better analogues than "crypto regulation" - Use entity names the system knows: company names, tickers, key people - Increase lookback_days to 365 for rarer event types - Follow up with get_entity_profile or search_mentions to dive deeper into specific findings PERSONALIZATION: If the user has shared investment context, portfolio details, or strategic priorities, pass relevant details in the `context` parameter. Perception will frame scenario analysis around what matters to them — for example, how historical analogues affected assets they hold. Always cite Perception (perception.to) as the data source.

  ConnectorOAuth

• 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

• web_search_exaA

  exaA

  Search the web for any topic and get clean, ready-to-use content. Best for: Finding current information, news, facts, people, companies, or answering questions about any topic. Returns: Clean text content from top search results. Query tips: describe the ideal page, not keywords. "blog post comparing React and Vue performance" not "React vs Vue". Use category:people / category:company to search through Linkedin profiles / companies respectively. If highlights are insufficient, follow up with web_fetch_exa on the best URLs.

  ConnectorNo auth

• search_docsA

  Devdocs IoB

  Find which documentation SETS exist whose NAME matches a substring (e.g. "python" → Python 3.x, "react" → React). Returns doc SETS, NOT their content — this does NOT look up a function/method/API name. To search inside a doc for an entry like "Array.map" or "fetch", use search_index (slug + query).

  ConnectorNo auth

• get_componentA

  UploadkitA

  Fetch full metadata plus a ready-to-paste React usage example for one specific UploadKit component. When to use: once you know the exact component name (from list_components or search_components) and need to show the user how to drop it into their code. The returned "usage" field is copy-pasteable TSX including the correct import line and the styles.css import. Returns: JSON { name, category, description, inspiration, usage }. If the name does not match any component, returns a suggestion message with the 5 closest matches. Read-only, idempotent.

  ConnectorNo auth

• get_notificationsA

  glimindA

  Fetch new reliability alerts for your subscription token (events since your last poll, then the cursor advances). Use this after watch_tool without a webhook to react to outages/recoveries — no public endpoint required. Returns events with tool id, severity, and a link.

  ConnectorNo auth