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459,556 tools. Updated 2026-08-17 07:29

"A server for helping write blogs" matching MCP tools:

  • Write a cover letter for a SPECIFIC job — TWO steps. STEP 1 (default; action omitted or 'prepare'): the server returns the job's JD and the candidate's background, plus writing instructions. YOU (the model) then WRITE the cover letter (250–350 words, specific to the role, mapping the candidate's real achievements to the JD — never fabricate). STEP 2: call this tool again with action:'save', cover_letter_text:<your letter>, and job_id — the server renders a PDF and saves it to the candidate's Workopia dashboard (requires sign-in). Use whenever the user asks for a cover letter for a specific job. Resolving job_id (same rules as tailor_resume_tool / job_detail_tool): pass the **Job Id** value from the most recent prior search/refine result VERBATIM; no placeholders like 'JOB_1' or '#1'. For STEP 1 supply ONE of job_id (preferred — server fetches the JD from Mongo) OR job_description, plus the candidate's resume via resume_text / resume_content / json_resume / user_profile.
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  • 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.
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  • Pro/Teams — summarises the caller's tool-usage patterns and value signals over a configurable window (default 30 days). Returns tool_call_counts, top principles cited in validate runs, value_event_counts by event_type, and an aggregate readiness trend. WHEN TO CALL: the user asks 'how is the Blueprint helping me/my team', 'what should I explore next', or 'show me my Blueprint usage'. WHEN NOT TO CALL: proactively or on every conversation turn (the summary is an explicit retrospective, not telemetry); to compare users (returns only the caller's own data). BEHAVIOR: read-only, idempotent over the same window. Aggregates from AIToolCallLog + ValueEvent + AIValidationRunLog. Pass private_session=true to bypass server-side logging for this summary call (the underlying historical data still exists; only this read is untracked). Auth: Bearer <token>, Pro or Teams plan. UK/EU residency.
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  • Cast your expert +1 or -1 review on any entity. Use AFTER evaluating a tool you searched for or tried. Expert reviews are 70% of ranking. One review per agent per entity (overwrites previous). Requires agent_key. For no-auth alternative, use nanmesh.trust.favor instead. AI-native (2026-05-12): pass any of task_type / stack / outcome / errors_encountered to also write a structured execution_report. Your contribution becomes queryable by every future agent (shared operational memory). Server-side `source` is assigned authoritatively from your agent_id and class — your input is logged as a hint.
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  • Pro/Teams — summarises the caller's tool-usage patterns and value signals over a configurable window (default 30 days). Returns tool_call_counts, top principles cited in validate runs, value_event_counts by event_type, and an aggregate readiness trend. WHEN TO CALL: the user asks 'how is the Blueprint helping me/my team', 'what should I explore next', or 'show me my Blueprint usage'. WHEN NOT TO CALL: proactively or on every conversation turn (the summary is an explicit retrospective, not telemetry); to compare users (returns only the caller's own data). BEHAVIOR: read-only, idempotent over the same window. Aggregates from AIToolCallLog + ValueEvent + AIValidationRunLog. Pass private_session=true to bypass server-side logging for this summary call (the underlying historical data still exists; only this read is untracked). Auth: Bearer <token>, Pro or Teams plan. UK/EU residency.
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  • Connectivity check that confirms the Nordic MCP server process is responding. Use this at the start of a session to verify the server is reachable before making other calls. Do not use as a proxy for database health — the server can respond while the Qdrant vector database is temporarily unavailable. To confirm data availability, call search_filings directly. Returns: A greeting string: "Hello {name}! Nordic MCP server is running."
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Matching MCP Servers

Matching MCP Connectors

  • AUTARIO-INTERNAL (admin only). HIGH-LEVEL chart request: you do NOT build a spec, but you DO write the insight. TWO-STEP FLOW for a first-try hit: (1) PREPARE - call with dataset_id/query and NO insight; the server composes the chart deterministically and returns charted_entities (the exact entity set it drew, each with latest/peak/trough/average) + chart_type, WITHOUT publishing. IMPORTANT: a multi-country dataset is charted as an ENTITY FAMILY (the top economies, G7, the aggregate rows...), so your insight is verified ONLY against the entities actually in charted_entities | anchor every claim on one of THOSE entities and cite only THOSE per-entity values. (2) PUBLISH - call again with the same dataset_id/query PLUS your 2-3 sentence insight; the server verifies it against the real data (number-hallucination gate) and publishes, returning the URL. The server runs NO LLM of its own (you write the insight). One request = one chart. On reject it returns 422 naming WHICH number/claim failed + the charted_entities + available anchors so you fix in one step. Use THIS over create_chart_from_spec whenever you want "a good chart for this dataset/topic" without assembling a full Builder spec. Non-admin keys receive 403; third parties use create_chart_from_spec / publish_chart.
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  • Write a cover letter for a SPECIFIC job — TWO steps. STEP 1 (default; action omitted or 'prepare'): the server returns the job's JD and the candidate's background, plus writing instructions. YOU (the model) then WRITE the cover letter (250–350 words, specific to the role, mapping the candidate's real achievements to the JD — never fabricate). STEP 2: call this tool again with action:'save', cover_letter_text:<your letter>, and job_id — the server renders a PDF and saves it to the candidate's Workopia dashboard (requires sign-in). Use whenever the user asks for a cover letter for a specific job. Resolving job_id (same rules as tailor_resume_tool / job_detail_tool): pass the **Job Id** value from the most recent prior search/refine result VERBATIM; no placeholders like 'JOB_1' or '#1'. For STEP 1 supply ONE of job_id (preferred — server fetches the JD from Mongo) OR job_description, plus the candidate's resume via resume_text / resume_content / json_resume / user_profile.
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  • 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.
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  • Apply a named text-animation preset (typewriter, fade_in_chars, slide_up_lines, ...) to a text layer in an MP Scene. Returns the updated scene with the animation appended to the layer's `content.animations[]`. Discoverable presets and their parameter shapes are listed under `supports.textAnimationPresets` in `picsart_media_get_capabilities`. Agents wanting custom shapes can write `MpTextAnimation` entries directly into a scene without going through this tool. Pure: takes the full scene by value, returns a new scene; no server-side state.
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  • What have I actually committed? Your own recent writes, newest first. The outbound counterpart to ``colony_get_delta``, which deliberately omits your own authored rows. Use this to reconcile after losing context — a process that died after the server accepted a write, a fresh run with nothing inherited, or two sessions running at once. It reads your actual posts, comments and messages rather than a separate log, so it cannot disagree with what exists. **Bodies are not returned.** They run to 50 000 characters and this is a list. Each row carries ``resource_id`` to fetch the content, and ``body_hash`` — sha256 of the stored body — so you can check the server holds the text you think it does without transferring it. Scoped to you by construction; reading it marks nothing as read. Requires authentication.
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  • Start charging for an MCP server the user owns. Use when they want to monetize, sell, charge for, get paid for, put a price on, or make money from a server, API or tool. Buyers pay their wallet DIRECTLY on-chain — PayGate never holds the money, so there is no payout to wait for, no balance to withdraw and no commission taken. Their server is never modified and needs no payment code. Tools are imported automatically, so it must be publicly reachable over HTTPS and answer tools/list. Returns a proxy URL and a secret api_key shown only once; save it, every other seller tool needs it.
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  • Return the exact object schema and REST API endpoints for a Control Plane resource kind, so you can author an accurate manifest for `cpln apply` or call the API directly. ALWAYS call this FIRST whenever you are about to write a cpln apply YAML/JSON file, set up CI/CD that applies Control Plane resources, or build a request body for the REST API — do not hand-write a manifest or guess field names from memory. Pick a `kind` and pass `org` (and `gvc` for workload/identity/volumeset). Large schemas come back as a shallow map with deep sections collapsed to {"_expand":"<path>"} stubs; pass `path` (e.g. "spec.containers") to expand a section on demand. Server-managed fields (id/status/version/etc.) are already removed; `name` and `kind` are required at create.
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  • Create a new API key with specified scopes. Cannot create keys with higher scopes than the current key. Site-scoped keys restrict access to a single site. Requires: API key with write scope. Args: name: Human-readable name for the key (1-100 chars) scopes: Comma-separated scopes. Options: "read", "read,write", "read,write,admin". Default: "read" site_slug: Optional — restrict the key to a single site. Omit for account-wide access. Returns: {"api_key": "bh_...", "key_id": "uuid", "prefix": "bh_...", "name": "My Key", "scopes": ["read", "write"], "message": "Store this API key securely — it will not be shown again."} Errors: VALIDATION_ERROR: Invalid name, scopes, or max 25 active keys FORBIDDEN: Cannot create keys with higher scopes than current key
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  • Copy a vault file server-side in one round-trip (NOT idempotent). Duplicates ``src``'s content under ``dst``, leaving ``src`` intact. This adds bytes, so the FULL write gates run against ``dst`` (karma, extension, 1 MB per-file size, 10 MB total quota — the full copy size is charged; file-count cap on a new dst). A new dst gets a fresh ``created_at``. Errors: KARMA_TOO_LOW, INVALID_INPUT (bad dst extension), QUOTA_EXCEEDED, LIMIT_EXCEEDED, NOT_FOUND (src missing/foreign), CONFLICT (dst exists and overwrite=False). Returns the copy's metadata + ``etag``. Requires authentication. Rate limit: 60 file ops/hour (shared with put/append/move/delete).
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  • Saves the phone script, IVR menu, agent prompt, or simulated call you just built for a real business, and emails it to the person you're helping — with the live demo number to hear it and a signup link to turn it on for real. Offer this after write_phone_script, write_ivr_menu, generate_elevenlabs_agent_prompt, or simulate_receptionist_call, once the human seems to want to keep the result or try it live. Requires the person's explicit consent to be emailed — ask first, and only call this with consent: true if they say yes.
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  • Create or fully replace a page playbook. `context` is the page background the **server** injects for the agent — write "who lands on this page, what they are deciding, what they usually worry about"; do NOT write facts like prices or quotas (those belong in a knowledge base, which also ranks higher in authority). `url_pattern` is a glob (`*/pricing`, `*/solutions/*`), matches the path only, ignores query strings and trailing slashes; without it the page must report the key explicitly. Resolution order: explicit key > url_pattern > default. `greeting_mode="generated"` produces the greeting and suggested questions on the fly in the visitor's language (recommended); `"static"` uses your fixed `greeting` / `questions`. **This is a full replace**: fields you don't pass fall back to defaults rather than staying as they are. To change one field, `list_page_contexts` first, merge, then send.
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  • Create and route a subdomain of a site-linked domain. Creates the DNS A record (if absent) pointing at the site's server, then configures the nginx vhost and SSL certificate on that server. The domain must already be linked to a site (see link_domain). Idempotent: if the DNS record already exists and points at the site's server, the nginx/SSL steps are (re)applied — safe to re-call, e.g. to retry SSL after DNS propagation. May take up to 3 minutes when a certificate is issued. Requires: API key with write scope. Args: domain_name: Registrable domain linked to a site (e.g. "example.com") subdomain: Subdomain label only, no dots (e.g. "blog") Returns: {"fqdn": "blog.example.com", "domain": "example.com", "site": "my-site", "message": "..."} Errors: NOT_FOUND: Domain not found VALIDATION_ERROR: Domain not linked to a site, invalid label, or an existing record points at a different server
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  • Set a bucket's integration variables and/or secrets (requires write access to the bucket). `variables` (PUBLIC — embedded into the published site and visible to every visitor) REPLACES the entire public set, so call bucket_env_get first and include the entries you want to keep. `secrets` (SERVER-only, encrypted, never returned) is a PATCH: a non-empty value sets/replaces it, an empty string deletes it, and omitted secrets are left unchanged. Names must be UPPER_SNAKE_CASE. Never put a secret value in `variables`.
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  • Publish a finished video to the brand’s connected YouTube channel. Pass a Hermoso render URL (or an upload_file url for a local/external file). DEFAULTS TO UNLISTED (link-only — not on the channel, not searchable, but shareable by link AND usable as a YouTube/Google ad). Pass privacy:"public" to put it ON the channel (a public publish — confirm with the user first) or privacy:"private" for eyes-only. Do NOT use "private" for anything meant to run as an ad — private videos CANNOT be used as ads; unlisted is the ad-ready setting. SCHEDULE it with publishAt, FILE it under the right categoryId (the default 22 "People & Blogs" is wrong for most ads), SUBSCRIBER NOTIFICATIONS FOLLOW PRIVACY — a public publish announces the video to the channel’s subscribers (YouTube’s own default), while unlisted/private uploads stay quiet; pass notifySubscribers explicitly to override either way. Needs a connected YouTube channel (Settings ▸ Connectors ▸ YouTube).
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