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261,244 tools. Last updated 2026-07-05 11:56

"A service for essay editing and feedback" matching MCP tools:

  • Report a problem with **the Partle marketplace API/MCP itself**. Authenticated. Prefer **OAuth**: connect once via the consent flow and the bearer token is attached automatically. **Fallback**: pass an `api_key` (prefix `pk_`, generate at /account). Required OAuth scope: `feedback:write`. Feedback is attributed to your account so reports are trustworthy and the channel can't be flooded anonymously. Scope — what this is for: - A Partle tool description is unclear or its parameters are surprising. - A Partle response is broken, malformed, or missing fields. - The Partle catalog is missing a category of products you'd expect. - Search relevance is off for a specific class of queries on Partle. Scope — what this is **NOT** for: - General complaints about tasks Partle isn't designed to do (Partle is a local-marketplace search/listing API — not a news API, an HTML hosting service, a portfolio-rebalancing app, a stock brokerage, or a generic dashboard SaaS). - Venting that an invented API key was rejected (Partle keys must be `pk_<hex>`; generate one at /account — don't fabricate them). - Asking the maintainers to do work the user requested but you can't do. If you can't fulfil a user request, tell the user — don't submit feedback about it here. Don't loop — each call adds a row and pages the maintainer. Resubmitting the same text within 24h is de-duplicated (returns the existing id). Args: feedback: Freeform text up to 5000 characters. Be specific — name the tool, the input that was confusing, and what you expected. api_key: Legacy/fallback auth. Omit when using OAuth. Returns: ``{"id": int, "message": "Thanks for the feedback!"}`` on success, or ``{"error": ...}`` on auth, rate-limit, or validation failure.
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  • Report a problem with **the Partle marketplace API/MCP itself**. Authenticated. Prefer **OAuth**: connect once via the consent flow and the bearer token is attached automatically. **Fallback**: pass an `api_key` (prefix `pk_`, generate at /account). Required OAuth scope: `feedback:write`. Feedback is attributed to your account so reports are trustworthy and the channel can't be flooded anonymously. Scope — what this is for: - A Partle tool description is unclear or its parameters are surprising. - A Partle response is broken, malformed, or missing fields. - The Partle catalog is missing a category of products you'd expect. - Search relevance is off for a specific class of queries on Partle. Scope — what this is **NOT** for: - General complaints about tasks Partle isn't designed to do (Partle is a local-marketplace search/listing API — not a news API, an HTML hosting service, a portfolio-rebalancing app, a stock brokerage, or a generic dashboard SaaS). - Venting that an invented API key was rejected (Partle keys must be `pk_<hex>`; generate one at /account — don't fabricate them). - Asking the maintainers to do work the user requested but you can't do. If you can't fulfil a user request, tell the user — don't submit feedback about it here. Don't loop — each call adds a row and pages the maintainer. Resubmitting the same text within 24h is de-duplicated (returns the existing id). Args: feedback: Freeform text up to 5000 characters. Be specific — name the tool, the input that was confusing, and what you expected. api_key: Legacy/fallback auth. Omit when using OAuth. Returns: ``{"id": int, "message": "Thanks for the feedback!"}`` on success, or ``{"error": ...}`` on auth, rate-limit, or validation failure.
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  • Read-only. Use to find workflows in a project by name, description, or trigger type before inspection or editing. Trigger filters include database, auth email, repeating, broadcast, and no-trigger workflows. Returns paginated workflow summaries, published/sandbox state, trigger type, workflow URLs, totalCount, hasMore, and nextOffset. Do not use as the final source of truth before editing; call get_workflow_and_preview_url for full structure.
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  • Sends the user's product feedback about agentView to an internal review queue. Use this ONLY when the user explicitly wants to share feedback, a feature request, a complaint, or praise about agentView itself (not about the content shown on a display). Always confirm the wording with the user before sending; never invent or embellish feedback on their behalf. Requires authentication with at least content_only scope. The feedback is stored for later review; no automatic reply is sent and this does not open a support ticket. Returns the new feedback id and a status of 'received'.
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  • File management operations that create or modify state: create a new file, open an existing file to start an editing session, or close a session. Requires authentication. Actions: • open_file(file_id?, file_name?) — Open a file by UUID or name and start an editing session. Returns the file's web URL. • create_file(file_name, team_uuid?) — Create a new blank spreadsheet. If team_uuid is omitted, the user's first team is used. Returns the new file's UUID and web URL; the file must be opened with open_file before it can be edited. • close_file(file_id) — Close an active editing session.
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  • Discover sheet names and used dimensions before reading or editing a WorkPaper. Returns metadata only; use read_range or read_cell for values.
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  • AI-to-AI petrol station. 56 pay-per-call endpoints covering market signals, crypto/DeFi, geopolitics, earnings, insider trades, SEC filings, sanctions screening, ArXiv research, whale tracking, and more. Micropayments in USDC on Base Mainnet via x402 protocol.

  • French public services: tax, property, admin, education, healthcare, security, risks, legal texts

  • Contribute data back to the KanseiLink community. Report success/failure after using a service (5 seconds, helps everyone), submit feedback, record API change events, or share your qualitative experience. PII is auto-masked. This is step 4 of the standard flow: search_services → lookup → (execute) → report.
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  • Search and list blog posts on erikbethke.com. Keyword queries match titles, summaries, tags, AND essay body text (body hits carry a snippet). Optionally filter by tag — umbrella tags like Policy expand to their members. Sorted by date descending; paginated.
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  • Deploys a Cloud Run service directly from local source files. This method is suitable for scripting languages like Python and Node.js, of which the source code can be embedded in the request. This is ideal for quick tests and development feedback loops. You must include all necessary dependencies within the source files because it skips the build step for faster deployment. **Key Requirements:** 1. source_code: Should set to sourceCode.inlinedSource.sources with array of source files, each having `filename` and `content`. 2. Size limit: you are subject to total request size limit of 50MiB.
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  • FEEDBACK: Submit feedback, bug reports, or feature requests to Luther Systems Use this tool to forward user feedback directly to the Luther Systems team. This includes bug reports, feature requests, questions, or general feedback about InsideOut. The agent itself can also use this tool to report issues it encounters during operation. REQUIRES: session_id, category, message OPTIONAL: user_email (for follow-up), user_name, source (default: 'mcp'), initiator ('user' or 'agent') Categories: bug_report, feature_request, general_feedback, question, security The 'initiator' field tracks who triggered the report: - 'user' — the user explicitly reported the issue or requested feedback submission - 'agent' — Riley detected an issue and initiated the feedback flow Examples: - User says 'the deploy button is broken' → submit_feedback(category='bug_report', message='...', initiator='user') - User says 'I wish it had dark mode' → submit_feedback(category='feature_request', message='...', initiator='user') - Deployment failed with Terraform error → submit_feedback(category='bug_report', message='Deployment failed: Terraform apply error on aws_alb resource — timeout waiting for ALB provisioning', initiator='agent')
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  • Send the course team feedback FOR the learner — what's confusing, a bug, an idea, or praise. No grade, no admin key. Use it the moment a learner is stuck or reacts to something, AND always offer it when a session wraps ('anything confusing, or that you wish it did?'). Routes to the team's Slack + the feedback log so friction becomes a signal instead of a 1:1 text.
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  • Submit the patient's response to the prior cue and get the next one — federally-sourced, audience-safety-checked, and re-sequenced on that feedback. REFUSES WITHOUT PRIOR-MESSAGE FEEDBACK (the moat): the engine will not advance a stream blind, returning 409 if you skip it. response_action is one of the accepted cue vocabulary (see the signal://catalog resource). Same idempotency_key + same feedback returns the cached cue; conflicting feedback under the same key returns 409.
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  • Post to the botcorpus agent forum (https://botcorpus.com/forum/). Use it to request a NEW FACT/topic (category "fact-requests"), propose a NEW SERVICE/vertical (category "service-feedback", topic "new-vertical"), flag a stale value, or discuss a corpus domain. Posting is free community participation — no paid key needed: with a community key (free key at https://botcorpus.com/wp-json/bc/v1/key/free, or paid) you post under a stable agent identity; with no key the post still goes live as a public, IP-rate-limited author. Reading is public. Always cite a fact id or source URL when claiming something is wrong.
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  • Report real-world usage feedback for a part (e.g. 'fabricated 5 boards at JLCPCB, footprint fit perfectly' or 'pad 3 misaligned'). Feedback is recorded publicly on GitHub and builds the part's field-proven trust score. Please report after actually using a part — both successes and problems help.
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  • Get Lenny Zeltser's expert criteria for reviewing an existing IR report. Returns focused guidance for constructive critique — what to check in each section, writing quality issues to identify, and how to frame feedback collaboratively. Includes rating-sheet items (lens taxonomy plus the IR-specific Information sheet) as concrete reference points for grounded feedback. This server never requests your report and instructs your AI to keep it local.
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  • Add a review/rating for a completed task. Rate the operator's work quality. This is separate from approve/reject — it records feedback. Requires authentication.
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  • Submit the patient's response to the prior cue and get the next one — federally-sourced, audience-safety-checked, and re-sequenced on that feedback. REFUSES WITHOUT PRIOR-MESSAGE FEEDBACK (the moat): the engine will not advance a stream blind, returning 409 if you skip it. response_action is one of the accepted cue vocabulary (see the signal://catalog resource). Same idempotency_key + same feedback returns the cached cue; conflicting feedback under the same key returns 409.
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  • Reject the current drafts on a campaign_contact with textual feedback (e.g. 'too formal, shorten to 2 sentences'). Resets generation_status to 'pending' so a new version is generated based on your feedback, which again waits for approval.
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  • Send structured feedback for a completed Firecrawl v2 job. Use this for endpoint-level feedback on `scrape`, `parse`, `map`, or `search` jobs when the job result was useful, partially useful, or failed to meet expectations. For search-result quality specifically, prefer `firecrawl_search_feedback` when available because it has search-focused guidance. This generic tool posts to `/v2/feedback` and accepts endpoint-wide signals: - **endpoint** — one of `search`, `scrape`, `parse`, or `map`. - **jobId** — the id returned by that endpoint. - **rating** — overall result quality: `good`, `partial`, or `bad`. - **issues** — stable lowercase issue codes such as `missing_markdown`, `bad_pdf_parse`, or `wrong_links`. - **tags** — optional lowercase tags for grouping feedback. - **note** — short human-readable context. Do not include huge page contents or raw scrape results. - **url**, **pageNumbers**, and **metadata** — small contextual fields that identify what the feedback refers to. Do not store multi-MB outputs in feedback. Use concise notes, issue codes, URLs, and page numbers. **Returns:** `{ success, feedbackId, creditsRefunded, creditsRefundedToday?, dailyRefundCap?, dailyCapReached?, alreadySubmitted?, warning? }` JSON.
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