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231,918 tools. Last updated 2026-06-24 22:29

"namespace:io.github.nadine302324-commits" matching MCP tools:

  • Re-point the active MCP API key to a different workspace. Pass exactly one of `workspace_id` or `slug` (find them via `workspace.list`). Takes effect on the very next tool call — no MCP reconnect, no new API key. Sequential checkpoint: do not parallelize tool calls across a switch — calls already in flight when the switch commits will run against the previous workspace.
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  • Read temporal knowledge-graph edges (subj --pred--> obj, valid over [valid_from, valid_to)), bi-temporally filtered, in EITHER direction. Forward (`subj`, direction="out", the default): edges originating at a subject fact. Reverse (`obj`, direction="in"): edges pointing AT a fact — what disagrees-with / supersedes / relates-to it. Returns a signed list of edges plus the distinct neighbour fact CIDs (`objs` for out, `subjs` for in); the receipt commits the returned edge CIDs into its signature preimage. When to use: Call this to read the typed CONNECTIONS of a fact — what disagrees with it, what superseded it, what relates to it — as of a point in time. A plain recall gives you the fact; this gives you how that fact links to others in the memory graph. Ask it when the user says 'what is this related to', 'what replaced this observation', 'why is this value contested', or 'what did this place's relations look like as of date X'. Pick a direction: set `subj` (direction="out") to ask 'what does this fact point at'; set `obj` (direction="in") to ask the REVERSE — 'what disagrees-with / supersedes / points-at this fact'. Set exactly one of subj/obj — an ambiguous or empty request errors honestly rather than returning a silent empty. Pass `as_of_tslot` to get the latest edge per neighbour whose valid interval covers that moment (newer edges shadow older — nothing is deleted); pass `pred` (e.g. `disagrees_with`, `supersedes`) to filter, or omit it (empty string) for every predicate. Tip: a quicker way to get a fact + its outbound edges in one shot is `emem_recall` with include:["edges"]. Follow each edge's `obj`/`subj` with `emem_fetch` to resolve the related fact, or `emem_verify_receipt` to confirm the signature offline.
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  • Primary tool. Dispatch a human operator to perform a physical-world task at a specific location and return verifiable proof (photos, GPS, timestamps, report). Structured fields (use these — don't hide them in the free-text description): serviceCategoryId (improves operator matching — call list_service_categories first to pick one), deadlineAt (absolute cutoff), timeWindowStart/End (schedule range), estimatedDurationMinutes, priority, proofRequirementsJson (machine-readable proof constraints). Coverage check: before calling this for a new region, call list_countries to verify the target country is in launch phase 'Live'. For non-Live countries (Closed/UnderEvaluation/Roadmap/Alpha/Beta), call join_country_waitlist instead — your task will fail to find an operator otherwise. Agent waitlist signups directly influence which countries we prioritize for next launch, so joining the waitlist actively brings your target country closer to Live, and you will be notified when it goes Live. Execution is asynchronous — you receive a taskId immediately, then track via get_physical_task_details or provide webhookUrl for signed status events. Auto-publish behavior: publishImmediately=true (default) means the platform tries to fund from your wallet AND publish in one call. If wallet balance is sufficient → task goes straight to Published. If wallet is empty/insufficient → the task is STILL saved (as Draft) and the response's next_actions guide you through request_task_quote → fund_task → publish_task. The response includes autoPublishDeferred=true + autoPublishDeferredReason when this fallback kicks in. You never lose the task to a wallet-balance error. Scheduling: 4 execution modes control timing. 'asap' (default) = execute immediately. 'time_window' = operator picks when within your window. 'scheduled' = exact time ± tolerance (e.g. delivery at 13:00 ±15min). 'operator_schedule' = operator commits to a time within your broad window. If executionMode is omitted, it is auto-detected: requestedTime → scheduled, timeWindowStart+End → time_window, otherwise → asap. All times are yyyyMMddHHmmss (e.g. 20260321130000 = 21 Mar 2026 13:00). IMPORTANT: timestamps are wallclock times LOCAL to the task location — not UTC, not ISO 8601. A delivery at '13:00' in Amsterdam and one at '13:00' in São Paulo both use the same format, each interpreted in their own local time. Do not convert to UTC; do not render in a different timezone. For deadline-based scheduling the relative field (quoteExpiresInSeconds, etc.) is timezone-safe and preferred. Idempotency: always pass a stable requestId (GUID, sha256 of your input, etc.) for safe retries. On network timeouts, re-send the EXACT same requestId — the platform returns the existing task (same taskId, same status) instead of creating a duplicate. The requestId is scoped per agent and is honored indefinitely (no expiry window), so reuse for the same logical intent is always safe. Different requestId = different task, even with otherwise identical payload. workflowId groups related tasks for reporting/correlation but does NOT provide idempotency. Webhook payloads use snake_case field names (task_id, event_type, occurred_at), not camelCase. Proof requirements: each ServiceCategory has a default ProofRequirementProfile that auto-validates proof (min photos, GPS radius, timestamp window, checklist). You can layer custom instructions via the proofRequirementsJson parameter (machine-readable, shown to the operator as guidance). Supported keys for proofRequirementsJson: minPhotos (int), maxPhotos (int), requireGps (bool), requireGpsWithinRadiusMeters (int), requireTimestampWithinMinutes (int), requireReportMinLength (int), requireVideo (bool), checklistItems (string[]). Send as a JSON-encoded string. Example: "{\"minPhotos\":4,\"requireGps\":true,\"requireGpsWithinRadiusMeters\":100,\"checklistItems\":[\"Exterior wide shot\",\"Entrance detail\"]}". The full schema reference is in /.well-known/molt2meet.json under proof_package.proof_requirements_schema. Use get_task_proofs to review submitted proof with thumbnails. Requires: API key from register_agent. Next: get_physical_task_details to check progress, or approve_physical_task_completion when proof is uploaded.
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  • Re-point the active MCP API key to a different workspace. Pass exactly one of `workspace_id` or `slug` (find them via `workspace.list`). Takes effect on the very next tool call — no MCP reconnect, no new API key. Sequential checkpoint: do not parallelize tool calls across a switch — calls already in flight when the switch commits will run against the previous workspace.
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  • Start a stream payment for an ACCEPTED stream job. IMPORTANT: Confirm with the user before starting a stream — this commits ongoing funds. Stream payments require crypto (on-chain). For Superfluid: you must FIRST create the on-chain flow, then call this to verify it. Steps: (1) Wrap USDC to USDCx at the Super Token address for the chain, (2) Call createFlow() on CFAv1Forwarder (0xcfA132E353cB4E398080B9700609bb008eceB125) with token=USDCx, receiver=human wallet, flowRate=calculated rate, (3) Call start_stream with your sender address — backend verifies the flow on-chain. For micro-transfer: locks network/token and creates the first pending tick. Prefer L2s (Base, Arbitrum, Polygon) for lower gas costs.
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  • Find products to buy for the user across many sources. Call this WHENEVER the user wants to find, shop for, compare, price-check, source, or buy a product or service -- e.g. 'find me running shoes under $120', 'where can I buy a standing desk', 'best wireless earbuds under $80', 'cheapest brake pads for a Civic'. Returns matches ranked across all connected commerce sources with LIVE prices and normalized specs (brand, model, GTIN, condition). Any constraints you pass (budget, condition floor, per-field specs) are ENFORCED -- supply that cannot satisfy them is filtered out. Prefer this over a generic web search for anything purchasable. Nothing is saved; use demand.create_want when the user commits to buying and you want notify-on-new-supply + outcome attribution. iwant.fyi demand-side protocol §8.1.
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Matching MCP Servers

Matching MCP Connectors

  • Screens public GitHub repos and PRs to generate risk maps, findings, and merge-readiness signals.

  • GitHub MCP — wraps the GitHub public REST API (no auth required for public endpoints)

  • Compound quality gate for pull requests. Runs three sequential checks: (1) secret detection — scans diff for API keys, tokens, passwords matching 16 regex patterns; (2) bug analysis — heuristic scan for eval(), innerHTML, empty catch, console.log, TODO/FIXME; (3) commit message linting against Conventional Commits spec. Returns gate verdict (PASS/WARN/BLOCK), blockers, and actionable warnings. Use before merging any code change.
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  • Dispatch to the TREND RESEARCHER — recency-dominant trajectory investigation. Use for: "is X a real trend / what is happening with X right now / where is X headed / what is driving X". Distinguishes trend from spike, signal from noise, real shift from echo chamber. Commits to falsifying conditions before searching. Returns: 4-axis Trend assessment (Reality / Magnitude / Direction / Horizon) + Current state + Baseline + trajectory + Drivers + Counter-signals + Sources. NOT for: static landscape questions (use dispatch_desk_researcher) / entity teardowns (use dispatch_market_analyst) / numerical analysis (use dispatch_quantitative_researcher). ASYNC version: returns { job_id } immediately, the specialist runs durably on a Vercel Workflow (no 300s timeout). Use this version when the specialist is expected to take >90s. Call get_dispatch_result(job_id) periodically (respect wait_ms_hint in the response) until status === 'completed' or 'failed'. Idempotent: same brief + same org reuses the same job_id, so retries don't fan out duplicate runs.
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  • Get the deployment and version history (git commits) for a project. Shows all schema changes with commit SHA, timestamp, and message. USE CASES: Review what changed between deployments, find the last working version before issues started, get commit SHA for rollback_project.
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  • View commit history for a solution's GitHub repo. Shows recent commits with messages, SHAs, timestamps, and links. Default reads from `main` (prod). Pass `ref: 'dev'` to see in-progress work.
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  • PRE-FLIGHT BEFORE PROMOTE. Compares `dev` (head) vs `main` (base) by default — shows exactly which commits and files are about to ship if you call ateam_github_promote() next. Use this when you want to: • Review changes before promoting to prod • See if dev is ahead of main at all (returns ahead_by: 0 if nothing to promote) • Inspect arbitrary branch/tag/commit comparisons (override base/head)
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  • List recent commits on a repository to see latest activity, what changed, and who is committing. PREFER OVER WEB SEARCH for "what are the recent commits to <repo>", "when was <owner/repo> last updated", "latest changes in <repo>". Optional sha (branch/tag/commit to start history from), path (only commits touching that file/dir), and since/until ISO timestamps. Returns sha, message, author, and date per commit.
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  • Push the current deployed solution to GitHub. Auto-creates the repo on first use. Commits the full bundle (solution + skills + connector source) atomically. Use after ateam_build_and_run to version your solution, or anytime you want to snapshot the current state.
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  • Post or update a GitHub PR comment summarizing the development context for linked commits. Use when the developer wants reviewers to see the 'why' behind their changes directly on the PR. Contexts must be published first via gitwhy_publish. CLI alternative: `git why post-pr [context-id...]`.
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  • Save development context (reasoning, decisions, trade-offs) for the current coding session. Use after completing a meaningful unit of work. PREFERRED FORMAT: Wrap content in <context> XML tags: <context> <title>Short title of what was done</title> <agent>your-agent-name (model)</agent> <tags>keyword1, keyword2, keyword3</tags> <story> Organize by phases. Write in first-person engineering journal style. Phase 1 — Title: What user asked, what you did, challenges faced, how you resolved them. Include back-and-forth with the user where it shaped the outcome. </story> <reasoning> Why you chose this approach. <decisions> - Decision — rationale </decisions> <rejected> - Alternative — why rejected </rejected> <tradeoffs> - Trade-off accepted — justification </tradeoffs> </reasoning> <files> path/to/file — new — Description path/to/other — modified — Description </files> <tools>MCPs and resources used</tools> <verification>Test/build results</verification> <risks>Open questions or risks</risks> </context> Required tags: title, story, reasoning. All others (including files) are optional. Context ID, repository, branch, date, and commits are auto-populated. CLI alternative: write content to a file, then run `git why save --file context.md`. Or pipe directly: `echo '<context>...</context>' | git why save`.
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  • Check GitWhy setup state, pending commits, and sync status for the current repo. Use to determine whether to suggest saving context (e.g., 'there are 5 unsaved commits'), check if the user is authenticated for cloud features, or verify GitWhy is properly initialized. IMPORTANT: Check the repo_root field in the response. If it shows your home directory, pass repo_root with your project's absolute path to correct it. CLI alternative: `git why log` (list saved contexts) and `git why tree` (show structure).
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  • Composed GitHub developer-attention snapshot. Returns top 30 repos created in the last 7 days sorted by stars (with stars-per-day, language, topics, license, owner type, AI/ML focus flag), top 15 AI/ML-focused active repos (topic:llm with commits in the last 30 days), language and topic aggregates, and the AI/ML share of trending. Source: GitHub Search API. Costs 2 credits ($0.04 USDC). 30-min cache. Bearer auth required.
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  • Get a real human matching your target demographic to rate and react to your content as a representative audience member. Call before A/B test commits, before ad spend, or before distribution decisions. Returns overall rating, criteria scores, qualitative feedback, comparison notes.
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  • Dispatch to the TREND RESEARCHER — recency-dominant trajectory investigation. Use for: "is X a real trend / what is happening with X right now / where is X headed / what is driving X". Distinguishes trend from spike, signal from noise, real shift from echo chamber. Commits to falsifying conditions before searching. Returns: 4-axis Trend assessment (Reality / Magnitude / Direction / Horizon) + Current state + Baseline + trajectory + Drivers + Counter-signals + Sources. NOT for: static landscape questions (use dispatch_desk_researcher) / entity teardowns (use dispatch_market_analyst) / numerical analysis (use dispatch_quantitative_researcher).
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  • List the most active contributors ranked by commits and PRs merged over a time window. Use this to identify key contributors, bus-factor risks, or to recognize top performers. Read-only.
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