"Drone" matching MCP tools:

• list_coverageA

  Ansvar: EU Compliance & Legal IntelligenceA

  Show which countries, frameworks, and legal domains are available. Use this BEFORE calling `search` when the user's topic doesn't name a jurisdiction (e.g., 'what does the law say about consumer protection'); then present the returned jurisdictions to the user or ask which applies. Examples: • 'Which countries do you cover?' → list_coverage() • 'Do you have German law?' → list_coverage(jurisdiction='DE') • 'What jurisdictions for NIS2?' → list_coverage(domain='cybersecurity') • 'Which countries have drone law?' → list_coverage(domain='aviation') (also accepts 'drone' / 'uas') Returns a `jurisdictions` array (each with `code`, `name`, `region`, `laws`, `provisions`, `domains`, `counts_complete`, and `uncounted_sources`) plus framework and source listings. An incomplete-count row also carries `coverage_note` explaining why. NOTE: `laws`/`provisions` are WHOLE-JURISDICTION corpus totals — the response's `count_scope` is `whole_jurisdiction`. Under a `domain` filter the jurisdiction list is narrowed to that domain but the counts are NOT domain-scoped; do not report them as a per-domain count. The domain-specific signal is the (domain-filtered) `sources`/`frameworks`.

  ConnectorOAuth

• start_workflowA

  Ansvar: EU Compliance & Legal IntelligenceA

  Begin a structured workflow selected from the live workflow registry. The registry covers threat and privacy modeling; enterprise, automotive, robot, rail, OT and UAS risk/TARA; DPIA and FRIA; regulatory, medical-device, drone and machinery gap analysis; tender review and audit; document review; SORA authorisation; vulnerability prioritisation; and deferral dossiers. Call list_workflow_types first: it is the authoritative source of exact ids, deliverables, required slots, variants, and availability for this caller. When a fresh registry snapshot is available, this tool's workflow_type input schema carries a caller-authorized enum; otherwise it remains a string rather than silently falling back to a stale catalog. The workflow engine guides the process step by step with quality gates. Each step's questions_for_user is advisory — answerable from context or uploaded documents; only steps returning requires_user_input=true carry the server-enforced human-input gate. Which types you can start is tier-fenced: free and solo include seven types (1 and 2 runs a month) — threat_model, gap_analysis with its gap_analysis_nis2, gap_analysis_dora, gap_analysis_cra and gap_analysis_ai_act variants, and dpia, each reported as JSON or as a watermarked html or pdf — at those tiers the framework argument accepts only nis2, dora, cra or eu_ai_act, and the base gap_analysis needs one of them; Premium adds the rest of the interview-grounded catalog — LINDDUN, the TARA families, FRIA and the jurisdictional DPIA and gap variants, SORA, the drone and OT types, machinery conformity, and enterprise risk — with 5 runs a month; document review, the tender family and adversary tabletop require Team or Company. A start SPENDS a run from the monthly allowance, and on free and solo a cancel does not hand an unused one back — name the workflow_type you intend to the user and get their OK before calling this, and check get_my_capabilities for what is left.

  ConnectorOAuth

• goal-attach-fileA

  Planner (proof-of-done)A

  Attach a small file (mockup, diagram, screenshot, PDF) to a GOAL as a description attachment — NOT evidence: it is not bound to any acceptance criterion, is never judged and never counts toward closing the goal. Returns {attachment.url, attachment.markdown}; paste `markdown` into the goal description (goal-update description) and the web UI renders images inline. contentBase64 is reliable only for payloads ≤ ~1 KB (long string arguments get truncated on the agent side before the request is sent). For anything bigger call goal-request-upload with goalId and stream the file with a single PUT — same result shape, no base64.

  ConnectorNo auth

• commentA

  Done BearA

  Write on a task's comment thread. `action: "add"` posts a comment, attributed to the connected user and visible to everyone in the workspace, so write it as a message to the user's teammates rather than a note to the user; nobody is notified. `action: "edit"` rewrites one of your own (only its author may, and it is then marked edited). `action: "remove"` deletes one permanently — comments have no Trash — so confirm with the user first. Read the thread with task_show and `include: ["comments"]`.

  Connector

  Destructive

  No auth

• attachmentA

  Done BearA

  Add a file to a task or remove one. `action: "add"` fetches the given HTTPS `url`: the server downloads it, verifies its size and type, and stores it, so the model never sends file bytes. Pass a stable idempotency_key and reuse it for retries so a lost response cannot upload the file twice. `action: "remove"` deletes the named `attachment`. Read a task's files with task_show and `include: ["attachments"]`. Limited to 10 attachments per task and 10 MB per file. Allowed types: images (jpeg, png, gif, webp, heic), PDF, CSV, Markdown, and plain text.

  Connector

  Destructive

  No auth

• projectA

  Done Bear MCPA

  Create or change a project. `action: "add"` creates one (name required). `action: "edit"` updates the named project: only the fields given change, and an empty string clears description or target_date. `action: "join"` puts it in the caller's Your projects sidebar list and `action: "leave"` takes it out. Read projects with get_context.

  Connector

  Destructive

  No auth

• commentA

  Done Bear MCPA

  Write on a task's comment thread. `action: "add"` posts a comment, attributed to the connected user and visible to everyone in the workspace, so write it as a message to the user's teammates rather than a note to the user; nobody is notified. `action: "edit"` rewrites one of your own (only its author may, and it is then marked edited). `action: "remove"` deletes one permanently — comments have no Trash — so confirm with the user first. Read the thread with task_show and `include: ["comments"]`.

  Connector

  Destructive

  No auth

• attachmentA

  Done Bear MCPA

  Add a file to a task or remove one. `action: "add"` fetches the given HTTPS `url`: the server downloads it, verifies its size and type, and stores it, so the model never sends file bytes. Pass a stable idempotency_key and reuse it for retries so a lost response cannot upload the file twice. `action: "remove"` deletes the named `attachment`. Read a task's files with task_show and `include: ["attachments"]`. Limited to 10 attachments per task and 10 MB per file. Allowed types: images (jpeg, png, gif, webp, heic), PDF, CSV, Markdown, and plain text.

  Connector

  Destructive

  No auth

• goal-attach-evidenceA

  Planner MCP — provable "done" for AI agentsA

  PRIMARY path to close a Grove goal: this is the ONLY tool that covers an acceptance criterion. Attach binary evidence (screenshot, log dump, API response, export) to an AC — call it once per criterion to satisfy the close gate. The subordinate goal-add-evidence-text only adds context for proofs with NO bytes (URLs to permanent external sources, manual repro descriptions) and does NOT cover an AC. Caption is optional but strongly recommended: state what the file captures and the reproduction conditions (URL/commit/session/inputs) so a third reviewer can reproduce. ⚠ PICK THE RIGHT TRANSPORT BEFORE YOU CALL THIS TOOL ⚠ • BEST for ANY file > ~1 KB raw — and the ONLY no-token path, so use it in a claude.ai / hosted-agent session that has no raw X-Auth-Token → call the sibling MCP tool `goal-request-upload` with this same criterionId. It returns a one-time {uploadUrl, expiresAt}; then stream the raw bytes with a single PUT: `curl -sS --fail --upload-file "/abs/path/to/file.png" "<uploadUrl>"` (optionally add -H "X-Content-Sha256: <hex sha256>" so corruption fails fast). No base64, no token — the signed ?t= ticket in the URL is the only credential, single-use, criterion-scoped. The PUT response is the same evidence JSON this tool returns. • ALTERNATIVELY, if you DO have the raw X-Auth-Token in your shell → the `planner-attach.sh` helper (zero-install bash, binary-safe). The MCP base64 path below is unreliable for non-trivial files: long string arguments get truncated or whitespace-corrupted on the agent side BEFORE the JSON-RPC request is sent. Measured 2026-05-20 on prod: a 4 KB PNG arrived at the server as 1874 decoded bytes (file_hash_mismatch); a 2 KB payload arrived with stray whitespace (failed base64_decode). The server itself accepts up to 25 MiB raw — the bottleneck is the agent-side serialisation of contentBase64, NOT the server. planner-attach.sh COPY-PASTE RECIPE (replace 3 placeholders, run in your shell): curl -sS https://planner.monopoly-gold.com/api/cli/planner-attach.sh \ | PLANNER_TOKEN="<same X-Auth-Token you use for MCP>" bash -s -- \ --criterion-id "<CRITERION_UUID>" \ --file "/abs/path/to/file.png" \ --caption "what is captured and the repro conditions" \ --created-by "<your agent id>" Where to get each value: - PLANNER_TOKEN: the very same token that is already in your MCP config under the X-Auth-Token header for the `planner` server. NOT a separate credential. - CRITERION_UUID: the AC id you got from goal-get / goal-list. Same UUID you would pass to this MCP tool. - file path: absolute path on YOUR (agent) machine — the script reads it locally and streams multipart. The planner server never sees your filesystem. The helper computes SHA-256 itself and ships it as `contentSha256`, so any in-flight corruption fails fast with HTTP 400 instead of poisoning the evidence row. Output on stdout is the same JSON shape this MCP tool returns; non-zero exit means HTTP ≥ 400 (stderr explains). Without curl/bash? Fall back to raw multipart: POST https://planner.monopoly-gold.com/api/criteria/<id>/evidence/file, header X-Auth-Token, form fields file=@..., contentSha256=..., caption, createdBy. • File ≤ ~1 KB raw → this MCP tool is fine. ALWAYS pass `contentSha256` (hex SHA-256 of raw bytes BEFORE base64). Without it, a silently truncated PNG looks valid to the MIME sniffer; the server cannot distinguish a truncated 4 KB PNG from a valid 1 KB one and the vision judge burns ~30s on broken bytes. With the hash, the server fast-fails with error=file_hash_mismatch and points back here at the multipart endpoint. Validates MIME whitelist (png/jpeg/webp/gif/pdf/txt/json/zip), per-file size cap (ATTACHMENTS_MAX_FILE_BYTES, default 25 MiB), per-project attachments quota. Returns evidence record + file URL + serverSha256.

  ConnectorNo auth

• goal-attach-fileA

  Planner MCP — provable "done" for AI agentsA

  Attach a small file (mockup, diagram, screenshot, PDF) to a GOAL as a description attachment — NOT evidence: it is not bound to any acceptance criterion, is never judged and never counts toward closing the goal. Returns {attachment.url, attachment.markdown}; paste `markdown` into the goal description (goal-update description) and the web UI renders images inline. contentBase64 is reliable only for payloads ≤ ~1 KB (long string arguments get truncated on the agent side before the request is sent). For anything bigger call goal-request-upload with goalId and stream the file with a single PUT — same result shape, no base64.

  ConnectorNo auth

• goal-moveA

  Planner (proof-of-done)A

  Move a goal to a different parent or project. Pass newParentId=UUID to reparent (inherits project from new parent), newParentId=null to make root. Optional projectId=UUID overrides the target project when making root (cross-project move to root). Cascades project change to all descendants. Prevents cycles.

  ConnectorNo auth

• goal-add-criterionA

  Planner (proof-of-done)A

  Append an acceptance criterion to a goal. The text must describe an observable check over an artifact (e.g. "GET /api/health returns 200 with {status:ok}"), not a subjective approval. Each criterion has a class: pre-merge (default — proved in CI / by attached evidence) or post-deploy (proved by an executable probe against the deployed prod instance). A post-deploy criterion MUST carry probeSpec {method, url, expect:{http_code, body:{field: expectedValue}}} — the request the runner sends and the answer it must get; without it the call is rejected with error=probe_required. Passing probeSpec alone implies probeClass=post-deploy. Grove mode: AC (class and probe included) can only be added while goal is in backlog (frozen once started), quality linter blocks high-severity issues. Standard mode: AC editable until goal is closed, linter is advisory. Returns criterion id, position, text, probeClass, probeSpec and any quality findings.

  ConnectorNo auth

• goal-attach-evidenceA

  Planner (proof-of-done)A

  PRIMARY path to close a Grove goal: this is the ONLY tool that covers an acceptance criterion. Attach binary evidence (screenshot, log dump, API response, export) to an AC — call it once per criterion to satisfy the close gate. The subordinate goal-add-evidence-text only adds context for proofs with NO bytes (URLs to permanent external sources, manual repro descriptions) and does NOT cover an AC. Caption is optional but strongly recommended: state what the file captures and the reproduction conditions (URL/commit/session/inputs) so a third reviewer can reproduce. ⚠ PICK THE RIGHT TRANSPORT BEFORE YOU CALL THIS TOOL ⚠ • BEST for ANY file > ~1 KB raw — and the ONLY no-token path, so use it in a claude.ai / hosted-agent session that has no raw X-Auth-Token → call the sibling MCP tool `goal-request-upload` with this same criterionId. It returns a one-time {uploadUrl, expiresAt}; then stream the raw bytes with a single PUT: `curl -sS --fail --upload-file "/abs/path/to/file.png" "<uploadUrl>"` (optionally add -H "X-Content-Sha256: <hex sha256>" so corruption fails fast). No base64, no token — the signed ?t= ticket in the URL is the only credential, single-use, criterion-scoped. The PUT response is the same evidence JSON this tool returns. • ALTERNATIVELY, if you DO have the raw X-Auth-Token in your shell → the `planner-attach.sh` helper (zero-install bash, binary-safe). The MCP base64 path below is unreliable for non-trivial files: long string arguments get truncated or whitespace-corrupted on the agent side BEFORE the JSON-RPC request is sent. Measured 2026-05-20 on prod: a 4 KB PNG arrived at the server as 1874 decoded bytes (file_hash_mismatch); a 2 KB payload arrived with stray whitespace (failed base64_decode). The server itself accepts up to 25 MiB raw — the bottleneck is the agent-side serialisation of contentBase64, NOT the server. planner-attach.sh COPY-PASTE RECIPE (replace 3 placeholders, run in your shell): curl -sS https://planner.monopoly-gold.com/api/cli/planner-attach.sh \ | PLANNER_TOKEN="<same X-Auth-Token you use for MCP>" bash -s -- \ --criterion-id "<CRITERION_UUID>" \ --file "/abs/path/to/file.png" \ --caption "what is captured and the repro conditions" \ --created-by "<your agent id>" Where to get each value: - PLANNER_TOKEN: the very same token that is already in your MCP config under the X-Auth-Token header for the `planner` server. NOT a separate credential. - CRITERION_UUID: the AC id you got from goal-get / goal-list. Same UUID you would pass to this MCP tool. - file path: absolute path on YOUR (agent) machine — the script reads it locally and streams multipart. The planner server never sees your filesystem. The helper computes SHA-256 itself and ships it as `contentSha256`, so any in-flight corruption fails fast with HTTP 400 instead of poisoning the evidence row. Output on stdout is the same JSON shape this MCP tool returns; non-zero exit means HTTP ≥ 400 (stderr explains). Without curl/bash? Fall back to raw multipart: POST https://planner.monopoly-gold.com/api/criteria/<id>/evidence/file, header X-Auth-Token, form fields file=@..., contentSha256=..., caption, createdBy. • File ≤ ~1 KB raw → this MCP tool is fine. ALWAYS pass `contentSha256` (hex SHA-256 of raw bytes BEFORE base64). Without it, a silently truncated PNG looks valid to the MIME sniffer; the server cannot distinguish a truncated 4 KB PNG from a valid 1 KB one and the vision judge burns ~30s on broken bytes. With the hash, the server fast-fails with error=file_hash_mismatch and points back here at the multipart endpoint. Validates MIME whitelist (png/jpeg/webp/gif/pdf/txt/json/zip), per-file size cap (ATTACHMENTS_MAX_FILE_BYTES, default 25 MiB), per-project attachments quota. Returns evidence record + file URL + serverSha256.

  ConnectorNo auth

• kirk_demo_uavA

  Kirk — Unsupervised Structural Change DetectionA

  Runs a curated demonstration of Kirk on a UAV example. Zero arguments. Returns real Kirk output against the same sealed engine that customer callers hit. Free, rate-limited. First-time users: call this to see what Kirk does before signing up. Purpose: Score n=30 jittered 50-element spectra per acoustic class (drone / bird / helicopter) through the sealed engine and surface per-class score-distribution statistics plus z-separations for the three class pairs. Demonstrates that the same sealed engine sha handles market microstructure and acoustic spectra with the same primitive. Use when: You want to see Kirk's cross-domain generalization without needing your own audio dataset. Do not use when: You have real feature vectors to score — use ``kirk_infer_legacy`` directly (arg: list of 50 floats). This tool's inputs are fixed synthetic spectra baked into the demo. Capability class(es): Demonstrates domain-agnostic mathematical primitive — the same engine sha handles kirk_score_book (L2) and kirk_infer_legacy (arbitrary 50-vector). Path fit: MCP demonstration surface only. Cost: 0 IU. Rate-limited 3/hour per IP. Returns: Dict with per-class ``drone`` / ``bird`` / ``helicopter`` blocks (each: ``mean``, ``sd``, ``n``, ``kirk_version``), ``z_separation`` (dict of drone_vs_bird / drone_vs_helicopter / bird_vs_helicopter in pooled-sd units), ``representative_scores`` (the three single-sample scores from the canonical un-jittered spectra), ``interpretation_hint``, ``provenance``, and ``synthetic_spectral`` flag.

  ConnectorNo auth

• list_workflow_typesA

  Ansvar: EU Compliance & Legal IntelligenceA

  Find the authoritative live structured-workflow registry. Call this before start_workflow instead of guessing an id from examples or a static catalog. It covers every deployed workflow family, including risk/TARA, DPIA/FRIA, regulatory and medical-device gap analysis, procurement, document review, drone/OT workflows, and vulnerability decisions. Each entry carries workflow_type, base_type, display_name, description, produces (the final deliverable), required_slots, overridable_configurable, legal-review state, plus gateway-added minimum_tier and available_to_caller fields. Every tier sees the full directory; which rows are marked available depends on the caller — free and solo the seven included rows (threat_model, gap_analysis with its NIS2, DORA, CRA and AI Act variants, dpia), Premium the interview-grounded rows (adding LINDDUN, TARA, FRIA, the jurisdictional DPIA and gap variants, SORA, drone/OT, machinery conformity, enterprise risk), Team and Company every live row. A row locked by TIER carries tier_caveat: which tier runs it, what that tier adds, and the upgrade URL — so a tier-locked row is never a bare false. Discovery service failures and malformed responses fail explicitly; no static list is returned as if it were live.

  ConnectorOAuth

• goal-request-ac-changeA

  Planner MCP — provable "done" for AI agentsA

  Request a change to an acceptance criterion. grounds=unreachable (default): the AC cannot be proven — requires ≥3 failed evidence attempts (weak/mismatch) with 0 matches. grounds=wrong_criterion: the AC measures the wrong thing (owner never approved this wording, or a revealed fact shows it tracks something else) — no failed attempts required, but you MUST pass quotedFragment: a verbatim slice of the criterion text you claim is wrong (checked against the stored text), and the reason must name the unapproved wording or the finding; difficulty alone is rejected. An LLM judge screens the reason either way. On pass, creates an escalation for the goal owner to resolve (edit AC text, split to sub-goal, drop AC without creating a child, or reject). Grove mode only, goal must be in_progress.

  ConnectorNo auth

• goal-createA

  Planner (proof-of-done)A

  Create a goal/task/milestone/habit in the planning tree. Two modes: grove (default) — enforces acceptance criteria gate on status transitions (AC required before ready_for_work, file-evidence per AC before done); standard — carries the same AC but without the evidence gate (advisory linting only). Returns the created goal with id, webUrl, mode, and nextStep hint. Every goal must belong to a project (pass projectId or inherit from parent).

  ConnectorNo auth

• goal-deleteA

  Planner (proof-of-done)A

  IRREVERSIBLY delete a goal and all its descendants (children, evidence, blockers). Prefer goal-update status=cancelled to preserve history, or goal-block to mark an obstacle. Use delete only for erroneous/duplicate entries. Returns the deleted title and children_deleted count.

  Connector

  Destructive

  No auth

• goal-update-criterionA

  Planner (proof-of-done)A

  Update an acceptance criterion: its text and/or its class + probe. probeClass=post-deploy requires an executable probeSpec {method, url, expect:{http_code, body}} (kept from the criterion when omitted and one already exists; otherwise error=probe_required); probeSpec alone implies post-deploy; probeClass=pre-merge drops the probe. Grove mode: only while goal is in backlog (frozen once started), quality linter blocks high-severity issues. Standard mode: until goal is done, linter is advisory. Returns updated criterion details (text, probeClass, probeSpec) and any quality findings.

  ConnectorNo auth

• goal-request-ac-changeA

  Planner (proof-of-done)A

  Request a change to an acceptance criterion. grounds=unreachable (default): the AC cannot be proven — requires ≥3 failed evidence attempts (weak/mismatch) with 0 matches. grounds=wrong_criterion: the AC measures the wrong thing (owner never approved this wording, or a revealed fact shows it tracks something else) — no failed attempts required, but you MUST pass quotedFragment: a verbatim slice of the criterion text you claim is wrong (checked against the stored text), and the reason must name the unapproved wording or the finding; difficulty alone is rejected. An LLM judge screens the reason either way. On pass, creates an escalation for the goal owner to resolve (edit AC text, split to sub-goal, drop AC without creating a child, or reject). Grove mode only, goal must be in_progress.

  ConnectorNo auth

• goal-resolve-escalationA

  Planner (proof-of-done)A

  Resolve a pending AC escalation. Owner decides: edit (provide new AC text), split (move AC to a child goal), drop (remove the AC outright, optionally with a linkedGoalId audit reference), or reject (agent must find another way). All prior evidence on the AC is deleted for edit/split/drop so the agent must submit fresh proof.

  ConnectorNo auth