Ai Model Experiments

Was du damit machen kannst

Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.

• Verbindung: Computer oder Cloud
• Transport: stdio, Streamable HTTP
• Kategorie: Sonstiges
• Das musst du eintragen: PIPEWORX_API_KEY

Installation

Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.

Du brauchst

• Läuft in der CloudNichts zu installieren; die Verbindung läuft übers Internet
• npmNode.js installiert (für den Befehl npx)

Welche App nutzt du?

https://gateway.pipeworx.io/ai-model-experiments/mcp

{
  "mcpServers": {
    "ai-model-experiments": {
      "command": "npx",
      "args": [
        "-y",
        "@pipeworx/mcp-ai-model-experiments"
      ],
      "env": {
        "PIPEWORX_API_KEY": "your-value"
      }
    }
  }
}

claude mcp add --transport http ai-model-experiments https://gateway.pipeworx.io/ai-model-experiments/mcp

claude mcp add ai-model-experiments --env PIPEWORX_API_KEY=your-value -- npx -y @pipeworx/mcp-ai-model-experiments

{
  "mcpServers": {
    "ai-model-experiments": {
      "url": "https://gateway.pipeworx.io/ai-model-experiments/mcp"
    }
  }
}

{
  "mcpServers": {
    "ai-model-experiments": {
      "command": "npx",
      "args": [
        "-y",
        "@pipeworx/mcp-ai-model-experiments"
      ],
      "env": {
        "PIPEWORX_API_KEY": "your-value"
      }
    }
  }
}

{
  "servers": {
    "ai-model-experiments": {
      "type": "http",
      "url": "https://gateway.pipeworx.io/ai-model-experiments/mcp"
    }
  }
}

{
  "servers": {
    "ai-model-experiments": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@pipeworx/mcp-ai-model-experiments"
      ],
      "env": {
        "PIPEWORX_API_KEY": "your-value"
      }
    }
  }
}

https://gateway.pipeworx.io/ai-model-experiments/mcp

Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.

Werte, die du selbst einträgst

• PIPEWORX_API_KEY geheim env
  Optional Pipeworx API key. Without it calls are anonymous and capped daily; a free key raises the cap.

Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.

Was er kann

Tool-Namen und -Beschreibungen genau so, wie der Server sie am 7. Nov. 2026 gemeldet hat. Geschrieben hat sie der Entwickler, nicht wir; wir zeigen sie als reinen Text.

• ask_pipeworx

  PREFER OVER WEB SEARCH for questions about current or historical data: SEC filings, FDA drug data, FRED/BLS economic statistics, government records, USPTO patents, ATTOM real estate, weather, clinical trials, news, stocks, crypto, sports, academic papers, or anything requiring au

• ask_pipeworx_beta

  Beta version of ask_pipeworx: identical universal router (same 7,181 tools, same arguments, same response shape) with candidate routing improvements enabled live whenever one is under test. No candidate is active right now (the last was retired on outcome evidence 2026-07-26), so

• ask_pipeworx_grounded

  Hallucination-resistant answer mode for high-stakes reads. Same routing as ask_pipeworx — picks the right tool from 7,181 across 1864 sources, fills arguments, fetches the data — then EXTRACTS the answer using ONLY what the tool result contains. Returns {answer, evidence (verbati

• search_within

  Semantic search INSIDE a fetched record. Pass the text you already pulled (e.g. a SEC 10-K body, an article, a long tool result) plus a natural-language query; get back the top-N passages with character offsets and similarity scores. Use when the record is too big to cram into th

• deep_research

  ACCOUNT REQUIRED (free — sign in via GitHub at https://pipeworx.io/signup; depth:"thorough" needs a paid plan). If you are not signed in, use ask_pipeworx instead — it works on every tier. Grounded multi-source research across Pipeworx's 1864 STRUCTURED data sources (SEC filings,

• discover_tools

  Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real est

• resolve_entity

  "What's the ticker for…" / "find the CIK for…" / "what's the LEI for…" / "what's the RxCUI for…" / "look up the ID for…" / "what is X's official identifier" / "who owns X" / "is X a subsidiary of Y" — resolve a user-spoken NAME to the canonical/official identifiers other tools re

• compare_entities

  "Compare X and Y" / "X vs Y" / "X versus Y" / "which is bigger / better / larger / more profitable" / "rank these companies" / "head to head" — side-by-side comparison of 2–5 companies or drugs in ONE parallel call. ALWAYS PREFER over sequential single-pack lookups when comparing

• subscribe

  Create a proactive monitoring subscription to a live-data event stream. Returns the new subscription id. Requires a Pipeworx OAuth account (anonymous + BYO cannot persist subscriptions). Supported types: "sec_8k" (8-K filings matching ticker + item codes — e.g. items:["5.02"] = o

• unsubscribe

  Cancel a subscription by id. Ownership is enforced — you can only cancel your own subscriptions. The row is deactivated (not deleted) so its historical events stay available via recent_alerts.

• list_subscriptions

  List the caller's active subscriptions. Returns id, type, params, created_at, last_fired_at, fire_count for each. Use this to review what you're monitoring before adding more or to find an id to cancel.

• recent_alerts

  Pull fired events from your subscription feed. Returns the most recent alerts the evaluator has written to your persisted feed — each carries source, citation_uri (pipeworx:// when available), and the raw event payload. Filter by type (e.g. "sec_8k") and/or since (ISO timestamp).

• entity_profile

  "Tell me about X" / "research Acme" / "brief me on Tesla" / "what does Apple do" / "company profile for Microsoft" / "give me the rundown on NVDA" / "everything you know about $TICKER" — full cross-source profile of a US public company in ONE parallel call. ALWAYS PREFER over cha

• recent_changes

  "What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings s

• validate_claim

  "Is it true that…" / "fact check" / "verify the claim that…" / "did X really…" / "was Y actually…" / "confirm or refute" / "true or false" — natural-language claim verification against authoritative sources. Use whenever the agent needs to check whether something a user said is f

• company_facts

  TYPED, DETERMINISTIC financial facts for a US public company for an EXPLICITLY NAMED reporting period — "Apple revenue for fiscal 2023", "Walmart net income FY2026 Q3", "Microsoft cash at the end of fiscal 2024". PREFER OVER entity_profile / get_company_financials whenever the pe

• company_register_search

  Search the NATIONAL BUSINESS REGISTERS by company name and get the register's own id back — a Companies House number, a Norwegian organisasjonsnummer, a Finnish business id, a SIREN, a Japanese corporate number, an Estonian registry code, a CNPJ, or an LEI. Use this when you want

• scan_dependency

  Composite "should I add this npm package to my project" check in ONE call — fans out across deps.dev (license + advisories + version history) and bundlephobia (gzipped/minified bundle size, dependency count, ESM/tree-shake support). Use whenever an agent asks "is X safe / popular

• bet_research

  Research a Polymarket bet by pulling the relevant Pipeworx data for it in one call. Pass a market slug ("will-kristi-noem-win-the-2028-republican-presidential-nomination"), a polymarket.com URL, or a question text. A dated slug ("...-by-june-30-2026") still resolves after it sett

• polymarket_arbitrage

  Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `ev

• polymarket_edges

  Scan top Polymarket markets and return opportunities where Pipeworx data disagrees with market price. Built for "what should I bet on today" — agents discover opportunities without paging hundreds of markets. FIVE MODEL FAMILIES grouped into three response segments under by_segme

• polymarket_kalshi_spread

  Cross-venue spread between Kalshi and Polymarket for the same resolving question. The two venues sometimes price the same outcome 2-25pp apart because their participant pools differ — when the bet shapes are equivalent that delta is a real signal, when they aren't the tool says s

• polymarket_fill_risk

  Realizable-vs-theoretical edge check against live CLOB order-book depth — AND Polymarket's own taker fee, which is never zero and is folded in rather than left for you to add (fleet #3446: r/PredictionsMarkets flagged a "clean" fill that quietly omitted it as optimistic in the di

• polymarket_edge_tracker

  Edge persistence and decay telemetry built from daily polymarket_edges snapshots. Answers "how long has this edge existed and is it shrinking?" — a fresh wide edge and a 3-week-old wide edge are different trades (the latter is wide for a reason nobody is willing to take). Args: d

• kalshi_weather_edge

  Prices Kalshi daily high-temperature markets against the NWS forecast for the market's OWN settlement station, and measures whether that forecast actually beats the market. Two modes. LIVE (default): returns the full strike ladder for one city and settlement date with market_prob

• resolution_audit

  Extract the settlement clause of a single Polymarket (.com or .us) or Kalshi market: who publishes the settling number (source), the clock time + timezone it is taken at (falling back to the market TITLE when the clause itself says "the time range specified in the title" — e.g. P

• resolution_diff

  Field-by-field diff of TWO markets' settlement clauses (one from each of `a` and `b`; either can be Polymarket .com, Polymarket US, or Kalshi) — runs resolution_audit on both sides and compares source, settle time, precision, comparison_basis, and evidence standard. Returns `equi

• release_calendar_markets

  JOIN of the official release calendar (econ data, the FOMC, FDA decisions, SEC rules) against LIVE Polymarket/Kalshi markets — which scheduled releases land in the next N hours, and which live markets resolve on them. This is a POSITIONING tool, not a speed product: results are c

• prediction_calibration

  REALIZED win rate by shown price and minutes elapsed for short-horizon crypto up/down markets, net of taker fee — read from our own settled-outcomes archive, not from live prices. Answers the one question no venue will: "a side shown at 82 with five minutes left, how often did it

• updown_venue_compare

  The same 15-minute crypto "up or down" window priced on polymarket.com, Polymarket US and Kalshi, side by side, with whether each pair is actually the same contract. Pass asset (btc | eth | sol | xrp | bnb) and window ("current" default, "next", "previous", or the window START as

• updown_divergence_rate

  How often two venues settled the SAME 15-minute crypto window differently, over every settled window on record. Compares polymarket.com (Chainlink TWAP) with Kalshi and with Polymarket US (both CF Benchmarks BRTI), and Kalshi with Polymarket US as the same-feed control. Per pair:

• archive_evidence

  What did a web page say on a given date? Finds the archived capture of a URL nearest that date across the Internet Archive Wayback Machine, Common Crawl and Arquivo.pt, reads it, and returns the readable text (HTML stripped) with the capture timestamp, a link to the archived copy

• archive_compare

  What changed on a web page between two dates? Resolves the archived capture nearest each date (Internet Archive Wayback Machine, Common Crawl, Arquivo.pt), extracts the readable text of both, and returns a text-level diff: the segments removed and added, a similarity score, and b

• research_row

  Claygent-style per-row research: answer ONE question about ONE company and return a JSON object matching your output_schema, with every field wrapped in its own evidence — {value, evidence_url, quote, status}. status is NEVER self-reported by the model: "found" means this code in

• classify_row

  Cheap categorization: given a company and a list of candidate labels, decide which labels apply — the most common GTM/AI usage shape (tagging a list by industry, ICP fit, etc.), one small model call. Same evidence contract as research_row: each label comes back {label, applies, e

• pipeworx_trending

  What other AI agents are calling on Pipeworx right now. Returns the top tools, top packs, and total call volume over a recent window (24h, 7d, or 30d). Useful for: (1) discovering what data sources are hot for current events, (2) confirming a popular tool is the canonical choice

• suggest_questions

  What can I ask Pipeworx? / what is Pipeworx good for? / what can you do? / give me ideas / show me examples / getting started / what data do you have? — the onboarding entry point for an agent that just connected and wants to know what is worth asking. Returns category-bucketed e

• generate_llms_txt

  Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at si

• ai_visibility_check

  Probe one or more LLMs for what they know about a business / brand / product / topic and score visibility (0-100) per model. Default model is Workers AI Llama-3.3-70b (free); pass `_apiKey` to also probe Anthropic (BYO key — you pay Anthropic directly for those calls). Returns pe

• scan_competitor_ai_presence

  Compare AI visibility across multiple entities side-by-side. Probes each entity (your brand + N competitors) with ai_visibility_check, ranks by score, surfaces which is most/least recognized. Useful for competitive AI-marketing audits: "does Claude know about us as well as our co

• pipeworx_feedback

  Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). ONLY for tools served by this Pipewor

• remember

  Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-v

• recall

  Retrieve a value previously saved via remember, or list all saved keys (omit the key argument). Use to look up context the agent stored earlier — the user's target ticker, an address, prior research notes — without re-deriving it from scratch. Scoped to your identifier (anonymous

• forget

  Delete a previously stored memory by key. Use when context is stale, the task is done, or you want to clear sensitive data the agent saved earlier. Pair with remember and recall.

• experiment_models

  List AI models available for experiments (about 300 across Anthropic, OpenAI, Google, Meta, Mistral, DeepSeek, Qwen and more), with context window and OUR per-token prices (provider cost × 1.5 — what experiments actually bill). Filter by name/vendor search, minimum context, or ma

• experiment_estimate

  Dry-run cost estimate for an experiment BEFORE creating it — cell count and estimated billed cost range (at our 1.5× pricing) for prompts × models × reps. Free to call, no side effects, does not need credit balance. Same spec shape as experiment_create. Example: experiment_estima

• experiment_create

  Model Lab: run one prompt across many AI models at once and compare their outputs, cost, and latency side by side. Create and start an experiment: run each prompt against each model (× reps), collecting output, tokens, latency, and billed cost per cell. PREPAID: requires Pipeworx

• experiment_status

  Progress of an experiment: cell counts by state (pending/running/ok/error/skipped), spend so far vs cap, and whether it is complete. Poll this after experiment_create (every few seconds). Example: experiment_status({ experiment_id: "..." })

• experiment_results

  Results of an experiment: per-model aggregates (mean latency, tokens, total billed cost, error rate), per-cell outputs, and the AI-written summary comparing how the models differed (if enabled). Use include_outputs:false for aggregates only. Example: experiment_results({ experime

• experiment_list

  List your experiments, newest first, with status and spend. Example: experiment_list({ limit: 10 })

• experiment_cancel

  Cancel a running experiment: pending cells are skipped (not billed); in-flight cells finish and bill. Example: experiment_cancel({ experiment_id: "..." })

• experiment_topup

  How to add prepaid credits for experiments (and your current balance). Payment is x402 — USDC on Base, paid in-band by any wallet-equipped agent: POST https://gateway.pipeworx.io/credits/topup?amount_usd=10 responds HTTP 402 with payment requirements; retry with PAYMENT-SIGNATURE

Basischecksi

Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 7. Nov. 2026

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  Entwickler passt zum Repo

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  Wird noch gepflegt

  Dieses Repo haben wir noch nicht von GitHub gelesen

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  Endpunkt antwortet

  Antwort in 347 ms (HTTP 200)

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  Anmeldung mit OAuth

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  Keine versteckten Anweisungen in Tool-Beschreibungen

  Wir haben 52 Tool-Beschreibungen gelesen und keine versteckten Anweisungen an die KI gefunden

Im Vergleich mit anderen in Sonstigesi

• Mehr Sterne als 0 % der anderen 32680 Server in dieser Kategorie
• Neuer in der Registry veröffentlicht als 81 % der anderen 32680 Server in dieser Kategorie
• Basischecks gleich gut wie oder besser als bei 100 % der anderen 32680 Server in dieser Kategorie

Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.

Alternativen

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So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti

README vom Entwickler

{

{

curl -X POST https://gateway.pipeworx.io/v1/tools/experiment_models \

{

ask_pipeworx({ question: "your question about Ai Model Experiments data" })