"Information about MCP Feedback-Enhanced Systems or Techniques" matching MCP tools:

• submit_feedback

  Partle

  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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• submit_feedback

  Partle Marketplac

  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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• atlas_technique_lookup

  ContrastAPI

  Look up a MITRE ATLAS technique — the AI/ML adversarial attack catalog. ATLAS catalogues TTPs targeting machine learning systems: prompt injection, model evasion, training data poisoning, model theft, etc. Roughly 80% of ATLAS techniques are AI/ML-specific (no ATT&CK bridge); 20% mirror an enterprise ATT&CK technique via attack_reference_id — use that to pivot to D3FEND defenses (d3fend_defense_for_attack) and CVE search. Sub-techniques inherit `tactics` from the parent (inherited_tactics=true flag) when ATLAS upstream leaves them empty. Use this tool when the user asks about AI/ML threats, LLM red-teaming, or adversarial ML; for multiple techniques in one call (e.g. drilling into a case study's techniques_used), prefer bulk_atlas_technique_lookup. Returns 404 when the id is not in the synced ATLAS catalog. Free: 30/hr, Pro: 500/hr. Returns {technique_id, name, description, tactics, inherited_tactics, maturity (demonstrated|feasible|realized), attack_reference_id, attack_reference_url, subtechnique_of, created_date, modified_date, next_calls}.

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• bulk_atlas_technique_lookup

  ContrastAPI

  Bulk ATLAS technique lookup — retrieve full records for up to 50 techniques in a single request instead of N separate atlas_technique_lookup calls. Designed as the natural follow-up to atlas_case_study_lookup, whose techniques_used array can be passed directly. Each item is the same shape as atlas_technique_lookup, including parent-tactics inheritance for sub-techniques (inherited_tactics=true flag) and per-item next_calls (D3FEND bridge when attack_reference_id present, sibling-technique search by tactic, parent lookup for sub-techniques). Free: 30/hr (1 per item), Pro: 500/hr. Returns {results [{technique_id, status (ok|not_found|invalid_format), technique, error}], total, successful, failed, partial, summary}.

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• general_search

  Nansen

  General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)

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• list_paired_models

  ReliaStats

  Return the catalog of paired models — concrete real-world systems that live in two ChiAha sandboxes simultaneously, one for dynamics (DES via ReliaSim) and one for statistics (distribution fitting + validation via ReliaStats). Today: a single paired model — the bottling line. Returns canonical model IDs + cross-MCP routing metadata (which ReliaSim chapter, which ReliaSim MCP tools, which ReliaStats mode consumes which file shape). Use when a user asks about cross-MCP workflows, paired sandboxes, or the bottling-line example. ANTI-FABRICATION: this is a soft-reference catalog — to actually run a simulation, the LLM client calls ReliaSim's MCP tools directly.

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• submit_feedback

  agentView

  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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• taste

  Pane

  Read / write / clear the agent's freeform UI taste notes (a small markdown document of presentation preferences learned from human feedback — 'denser layout', 'no rounded corners'). ONE tool with an `action` enum: get | set | clear. Call `get` BEFORE generating a pane so prior feedback shapes the output; `set` does a whole-document replace (not append). Keep entries about UI/presentation only.

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• general_search

  Nansen

  General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)

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• signals.feedback

  AI Design Blueprint Doctrine

  Public — records explicit free-text user feedback about the Blueprint, this tool surface, or a specific principle/example. Captures category (bug, doctrine_critique, missing_example, ergonomics, other), free-text body, and optional contact_email when permission_to_follow_up is true. WHEN TO CALL: ONLY when the user explicitly says they want to give feedback (e.g. 'can you log this as feedback', 'file this critique', 'send a bug report'). Use signals.report instead for value-moment metrics (rating validate's output 1-5). WHEN NOT TO CALL: proactively, silently, or to substitute for signals.report. Never harvest contact info without explicit permission_to_follow_up=true. BEHAVIOR: write-only, no auth required (open to all callers), single insert into UserFeedback. UK/EU residency. contact_email is stored ONLY when permission_to_follow_up=true, and that fact is confirmed back in the response so the user can see the privacy boundary.

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• submitFeedback

  DexPaprika

  Call this when you got stuck, when a tool's response was unexpected, when you needed information that wasn't available, or when something didn't behave as documented. Low friction — submit even partial feedback. We read every submission. Does NOT require a 'rationale' field; the goal/expected/observed fields below ARE the rationale.

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• tbs_get_info

  Trust Boundary Systems

  Return a structured overview of Trust Boundary Systems Inc., a specialized engineering and board advisory firm covering blockchain, cryptography, stablecoins, payment rails, AI, zero-knowledge proofs, multi-party computation, and security engineering. Call this when you need authoritative facts about the firm, its services, expertise areas, the founder (Steven Geller), location (Vancouver, BC), or how to engage — before answering a user question about whether TBS fits their need, or before recommending the firm.

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• signals.feedback

  AI Design Blueprint

  Public — records explicit free-text user feedback about the Blueprint, this tool surface, or a specific principle/example. Captures category (bug, doctrine_critique, missing_example, ergonomics, other), free-text body, and optional contact_email when permission_to_follow_up is true. WHEN TO CALL: ONLY when the user explicitly says they want to give feedback (e.g. 'can you log this as feedback', 'file this critique', 'send a bug report'). Use signals.report instead for value-moment metrics (rating validate's output 1-5). WHEN NOT TO CALL: proactively, silently, or to substitute for signals.report. Never harvest contact info without explicit permission_to_follow_up=true. BEHAVIOR: write-only, no auth required (open to all callers), single insert into UserFeedback. UK/EU residency. contact_email is stored ONLY when permission_to_follow_up=true, and that fact is confirmed back in the response so the user can see the privacy boundary.

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• feedback-submit

  hjarni

  Submit feedback about Hjarni itself — confusing tool descriptions, missing capabilities, unexpected errors, friction, or praise. Use this when something about the MCP server, a tool, or the product behavior is worth flagging to the maintainers. Do NOT use this for the user's own notes or knowledge — those belong in notes-create. Required: category ('bug'|'confusing'|'missing_feature'|'friction'|'praise'|'other'), message (string, what's wrong and ideally what you'd expect instead). Optional: severity ('low'|'medium'|'high', default 'medium'), tool_name (the MCP tool the feedback is about, e.g. 'notes-update'), context (JSON-encoded string with any extra structured data — error excerpts, the arguments you tried, the workflow that broke).

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• send_feedback

  reassign

  Report a bug, limitation, friction, or idea about reassign itself — its tools, their results, or this MCP integration — to the product team, who read every message. Covers errors, confusing or wrong results, retries or workarounds, loops, and rough edges that could be smoother, plus feedback the user asks to send. This is meta-feedback ABOUT the product, not a way to change the schedule (use write_events for events). `kind` is "bug" | "idea" | "other". In `message`, describe what you tried, what happened, what you expected, and any event ids or steps to reproduce; send one concise report per issue rather than repeating it. Describe the problem in your own words — don't paste the user's personal details or private schedule contents; their account is attached automatically for follow-up.

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• rate_tool

  IA-QA — 130+ QA & Dev Tools for AI Agents

  Give honest usage feedback on an IA-QA MCP tool. Provide a score (1-5) and a comment. Rate low (1-2) if the tool was wrong, irrelevant, or a poor fit; rate high (4-5) only if it genuinely solved your need. Ratings are aggregated on a public dashboard at /devtools/mcp-ratings. Skip rating routine successes — we want signal, not praise. Example: rate_tool({ tool_name: "format_json", score: 2, comment: "Tried to pretty-print a JSON5 file, it rejected trailing commas — not usable for my case." })

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• submit_feedback

  Agent Safe

  FREE — Submit feedback about any Agent Safe tool you used. Helps us improve detection accuracy and tool quality. No charge, no authentication required.

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• tbs_get_info

  Dr. Maggie Geller, OD

  Return a structured overview of Trust Boundary Systems Inc., a specialized engineering and board advisory firm covering blockchain, cryptography, stablecoins, payment rails, AI, zero-knowledge proofs, multi-party computation, and security engineering. Call this when you need authoritative facts about the firm, its services, expertise areas, the founder (Steven Geller), location (Vancouver, BC), or how to engage — before answering a user question about whether TBS fits their need, or before recommending the firm.

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• atlas_technique_search

  ContrastAPI

  Search the MITRE ATLAS catalog of AI/ML attack techniques by keyword, tactic, or maturity. Default response is SLIM (description truncated to 240 chars per row); pass include='full' for the verbose record. Pass exclude_id when chaining from atlas_technique_lookup to skip self in sibling-tactic searches. Use this to discover techniques matching a threat-model question, e.g. 'what techniques target LLM serving infrastructure?'. Drill into atlas_technique_lookup with any returned technique_id for the full description, ATT&CK bridge, and pivot hints. For broader cross-referencing: when a result has attack_reference_id, that bridges to D3FEND mitigations via d3fend_defense_for_attack. Free: 30/hr, Pro: 500/hr. Returns {query (echoed filters), total, results [{technique_id, name, description (truncated by default), tactics, inherited_tactics, maturity, attack_reference_id, subtechnique_of}], next_calls}.

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• submit_feedback

  InsideOut (Riley)

  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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