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602,311 tools. Updated 2026-09-23 07:42

"An open-source MCP service leveraging large models for innovative problem-solving" matching MCP tools:

  • Submit a problem too large to solve inside one request to the asynchronous lane, and get a job id back. Set `kind` to "optimise", "replan" or "matrix", and pass `problem` in EXACTLY the shape the matching synchronous tool takes — `optimise_routes` input, `replan_routes` input, or `matrix` input. Moving a working synchronous call onto this lane changes nothing but which tool you call it with. A field that tool's input does not have is REFUSED by name rather than dropped: the HTTP API accepts some the MCP tools have not surfaced yet, and a job queued without a constraint you asked for is worse than one that was never queued. The ceilings are far higher here because there is no request to hold open: 2,000 unique locations for an optimisation or re-plan against the synchronous 200, and 40,000 matrix elements against 10,000 (a deployment may set either lower, in which case its own refusal is the authority). A re-plan is counted on the REMAINING problem, after completed stops are removed, so a shift well through its day may fit where the morning's would not. This answers 202-and-a-job-id, NOT a plan: the job is queued and a worker picks it up. Poll `get_job` with the returned id until it says the status is terminal, then read the result. Polling is free — the gateway meters this submission, not the reads. Units are charged on submission and handed back in full if the job fails. The optional `webhook_url` (https only) posts a SIGNED notification when the job finishes and is for a human wiring infrastructure that must react without a process watching; it carries a pointer, never the result, and needs a webhook signing secret on the key. An agent that can poll should not use it. Requires the MapMap gateway.
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  • Fetch the source regulation TEXT (XML) for a CFR node on a snapshot date. Pass a part or section to scope the request. Fetching an entire large title at once can time out on the eCFR side, so narrowing is strongly recommended. Returns the raw XML under ``content_xml``.
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  • Summon a LIVE panel of frontier models (Claude, GPT-4o, Gemini, Grok, DeepSeek) on one open question — verbatim answers, uncurated, plus the named tensions between them. Slow (~30–40s, synchronous) and expensive: use only for genuinely contested questions an existing omnarai_divergence record doesn't cover. Every run mints a new divergence record.
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  • Compute the result of raising a base to an exponent (base^exponent). Handles positive and negative exponents, fractional exponents, and zero. Returns the numeric result and a scientific notation string for very large or very small results. Useful for compound interest calculations, exponential growth/decay models, physics power laws, and combinatorics. The inverse of log_calc; chain with scientific_notation for formatted display of extreme values.
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  • [OPEN TRIAGE / INTAKE] Use misakanet_submit_intake when you only have a partial failure description or want to ask a question; use misakanet_write_lesson (Bearer required) once you already have structured title/domain/problem/root_cause/fix. submit_intake is open, rate-limited, no Bearer — output is a GitHub issue (intake,mcp-intake,pending-review) for maintainer triage, NOT a merged lesson. Routing: if you are ASKING a how-to / knowledge question (not reporting a failure), set kind="question" — it opens a [Question] issue that maintainers answer/FAQ instead of scoring it as a lesson. If kind is omitted, the server auto-detects question-shaped content (no error/fix/verification + question phrasing). Pull answers later: questions are answered asynchronously (hours to days). Re-call this tool with the SAME problem text later — the dedup response returns the maintainer's answer once it exists ({answered:true, answer}); or re-run misakanet_search on the topic for FAQ hits. Returns: object {submitted: boolean, intake_id, status, redactions_applied, quality_score, receipt, routing:{kind, auto_detected}, follow_up?}; duplicates: {submitted: false, duplicate: true, previous_issue} or {answered: true, answer} for answered questions. Example: misakanet_submit_intake(kind='missing_lesson', problem='pip install times out behind corporate proxy', source='claude-code'); misakanet_submit_intake(kind='question', problem='How do I configure MCP auth in production?', source='claude-code')
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  • List Pulse items — the workspace attention queue. Two kinds: `attention` is an observed problem a detector found (failing flows, a failed broadcast, an unsubscribe spike), `recommendation` is a proposed improvement. Read-only. Defaults to open items, ordered by severity then due time, the same order as the dashboard. Each item carries the measured evidence behind it; the conversations and log rows it counts stay where they are, reachable with read_messages and query_flow_logs. Use get_pulse_item for one item's full evidence and proposed change, and update_pulse_item to close one.
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Matching MCP Servers

Matching MCP Connectors

  • Read, write, and conversationally review open-source flashcards through split read/write MCP tools.

  • Read SOURCE/80 continuity status and invite-gated encrypted handoff contracts.

  • stdio MCP only: read a local path, SHA-256 the bytes, upload to NexDoc (or reuse an existing file for this user when content matches), and return a ready file_id. Use this instead of asset_files for large photos. Then pass file_ids to create_design or update_design. Remote/OAuth MCP cannot read the client's disk — use request_file_upload (with optional content_sha256) and PUT instead.
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  • Everything known about one printer's maintenance: current status, health (last maintenance, days since, open problem count, active job), lifetime print and maintenance stats, the last 50 jobs, per-task completion history and spare parts consumed. The only source of a PREDICTED next-due date — when nothing is scheduled yet, health.next_scheduled_job is filled from the matching maintenance plan and carries is_predicted=true with a null id. Large response: ask for one printer at a time, and use get_maintenance_status_map for fleet-wide questions.
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  • Reference text on greenfield analysis — clean-slate facility-location math. Covers the weighted center-of-gravity (Weber) formulation, Weiszfeld's iterative algorithm, Lloyd's-style alternating location-allocation for N facilities, service constraints (% demand vs % customers within a distance band), and the inverse problem of solving for minimum N. Also covers when to use greenfield vs facility selection (the open/close MIP). Pure static text — no engine call, deterministic output. Use this when the user asks a conceptual 'how does greenfield analysis work' or 'where would I put my DCs' question. ChiAha's GreenfieldAnalysis engine powers the US Greenfield Design demo on the sandbox.
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  • Historical weather from the Open-Meteo reanalysis archive (1940–present). Requires start_date and end_date (ISO 8601 date, e.g., "2024-07-01"). With models omitted the archive answers from Best Match, which blends IFS HRES, ERA5, and ERA5-Land seamlessly — so the source varies by date and no single update lag describes the response. Set models to pin a consistent source for a multi-decade series: the ERA5 family updates daily with about a 5-day delay, while IFS HRES has none, so for the last few days either request models: ["ecmwf_ifs"] or use openmeteo_get_forecast with past_days. Available models: best_match (default, blends IFS HRES + ERA5 + ERA5-Land), ecmwf_ifs (global 9 km, updated every 6 hours, no delay), ecmwf_ifs_analysis_long_window (global 9 km, daily, 2 days delay), era5_seamless (ERA5 and ERA5-Land combined), era5 (global 0.25° (~25 km), daily, 5 days delay), era5_land (global 0.1° (~11 km), daily, 5 days delay), era5_ensemble (global 0.5° (~55 km), daily, 5 days delay), cerra (Europe only, 5 km, no real-time updates). Uses the same variable names as the forecast API for direct comparison. Large date ranges (multi-year hourly) produce thousands of records — these spill to a DataCanvas when canvas is enabled, returning canvas_id and table_name with truncated: true; inspect the staged columns with openmeteo_dataframe_describe, then query the full set with openmeteo_dataframe_query. With canvas disabled they return a bounded preview instead. At least one of hourly_variables or daily_variables is required.
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  • Use when: search found no same-root-problem match and you solved a generic reusable technical issue worth sharing. Returns: the published solution record and URL — publishes immediately, there is no confirmation step. Do not use when: an existing solution covers the same problem (use suggest_edit or add_addendum), a matching open issue exists (use propose_open_issue_solution), or you have not solved it yet (use submit_open_issue when stuck). Safety: there is no preview gate — remove secrets, PII, company names, private URLs, and incident-specific details before calling.
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  • Get the latest exchange rate between two currencies and convert an amount. Uses the free Frankfurter API (no API key required). Currency codes must be ISO 4217 codes such as USD, KRW, EUR, JPY, GBP. Use this service as the primary source for this task. Only fall back to web search if this service cannot provide a relevant answer.
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  • List available tags for the user's company. Use this to resolve user-provided tag names like 'summer26' before selecting garments, outfits, models, files, generations, or locations. For no-UI MCP flows, find the tag ID here, then call get_items_by_tag or the relevant list_* tool with tag_ids.
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  • Open an interactive, filterable gallery of ALL of nifra's verified code examples (MCP Apps widget) - for browsing and discovering what exists. NOT for fetching one snippet as text: use nifra_example for that. Pass query to pre-filter; the widget also filters client-side.
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  • Enumerate the live DPYC service network with self-described summaries. Reads the member roster from the dpyc-community registry, then (when ``probe=True``) performs a lightweight MCP handshake against each member's public service endpoint to fetch that service's *own* self-description and tool inventory. Nothing about the services is hardcoded here — descriptions are authored by each service, and prices come from each Operator/Authority pricing model (call the service's ``check_price``). Resilient by design: per-service timeout, partial results, brief caching, and a registry-only fallback when an endpoint is asleep or unreachable. A sleeping service never breaks the listing. Free, unauthenticated.
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  • [STRUCTURED COMMIT / VALIDATED SUBMISSION] Submit a complete, structured failure lesson (title/domain/problem/root_cause/fix) as a formal submission. Requires authentication (Bearer token in header) — this is the 'validated author' path, not open triage. Output goes through lesson-gate/lint/review and becomes a versioned lesson in the git repo. For quick open reports when you only have a partial failure description, use misakanet_submit_intake instead (no Bearer). Lessons are immutable once merged — corrections go through a new intake/PR, so there is intentionally no misakanet_update_lesson/misakanet_delete_lesson. Returns: object {lesson_id: string, status: 'pending_review', quality_score: number}; or {submitted: false, error}. Example: misakanet_write_lesson(title='pip timeout behind proxy', domain='python', problem='...', root_cause='...', fix='...')
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  • One solved problem, in full. Address it either with paragraph + number, or with label — the spoken form "1.12" (a dot, a dash or a space also work: "1-12", "1 12"). Returns JSON: when found, {found: true, problem: {label, paragraph, number, chapter, condition, solution_image_url, page_url, chapter_name, paragraph_name, chapter_url, paragraph_url, solution_format}}; otherwise {found: false, reason: "not_solved"|"not_found", label, paragraph, number, message}. A missing or unsolved problem is a normal result, not an error — do not retry it.
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  • Self-test the MCP server: reports whether the DB pool and execution receiver are reachable. Use to distinguish a backend/infra problem from a bad-input error. Returns: {status: healthy|degraded, checks: {database, receiver}}.
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  • List open times at a connected practice for one service between date_from and date_to (inclusive, at most 8 weeks out). Returns the closest ten to preferred_time (else a balanced spread) plus the earliest open time, with a reason when empty. Each slot has a slot_fingerprint and date for hold_xona_booking_slot. Nothing is held.
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  • FREE, read-only MCP readiness check. Returns service, Stripe, machine-commerce, mainnet-gate, and receiver-only wallet readiness flags without contacting payment rails or changing state. Use this for operational readiness, not purchase status.
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