Forecast Accuracy & Track Record MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| APIFY_TOKEN | Yes | Your Apify API token. Required for the local stdio proxy server and for sending an Apify API token as a Bearer token to the hosted endpoint (otherwise sign in with Apify via OAuth). The token is only sent in the Authorization header and is never logged. | |
| APIFY_ACTORS | No | Optional comma-separated subset of the Actors to expose as tools (e.g. publicrecords/calibration-ledger,scrapemint/stock-earnings-estimates). | |
| APIFY_MCP_URL | No | Optional full endpoint override for the hosted Apify MCP server URL. |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| publicrecords--calibration-ledgerA | Calibration Ledger — trust a forecast, with evidence (beta). Given a claim from an organization (IMF, OECD, Fed/FOMC, SPF, ECB SPF, or a listed issuer), returns that organization's track record: error distribution, intervals, bias, band coverage, worst misses with source links — or honest 'no coverage' (free). Organizations only, never people. When to use: Use when someone cites a forecast from an institution (IMF, OECD, Fed/FOMC, SPF, ECB SPF or a listed issuer) and you need to know how accurate that institution's past forecasts were. Returns error distribution, bias and worst misses with source links, or an explicit no-coverage answer. Returns: the run's dataset rows as structured JSON (one row per result), plus the run and dataset IDs for paging the full dataset. Behavior: starts one run of the Apify Actor "publicrecords/calibration-ledger" through Apify's hosted MCP gateway (mcp.apify.com) with your own APIFY_TOKEN; the run uses your Apify account. Read-only: it only reads public web data and changes nothing on the source site. Docs: https://apify.com/publicrecords/calibration-ledger |
| pintostudio--economic-calendar-data-investing-comA | Economic Calendar Data (Investing.com). Extract structured economic calendar events (actual, forecast, previous, importance) from Investing.com across 45+ countries. Built for algorithmic trading systems, AI trading agents, RAG pipelines, and financial research. Filter by country, importance, category, and date range. When to use: Use when you need scheduled macro releases with actual vs forecast vs previous values (Investing.com economic calendar) by country, importance and date range. Returns: the run's dataset rows as structured JSON (one row per result), plus the run and dataset IDs for paging the full dataset. Behavior: starts one run of the Apify Actor "pintostudio/economic-calendar-data-investing-com" through Apify's hosted MCP gateway (mcp.apify.com) with your own APIFY_TOKEN; the run uses your Apify account. Read-only: it only reads public web data and changes nothing on the source site. Docs: https://apify.com/pintostudio/economic-calendar-data-investing-com |
| scrapemint--stock-earnings-estimatesA | Stock Earnings Estimates & Results: EPS Forecast vs Actual. Keyless earnings data for any US stock from NASDAQ: what analysts expect the company to earn next quarter, what it actually earned in past quarters, the percentage it beat or missed by, how often it has beaten, and whether analysts raised or cut their forecast in the last four weeks. When to use: Use when you need analyst EPS estimates vs reported earnings for a US stock, beat/miss history and recent estimate revisions. Returns: the run's dataset rows as structured JSON (one row per result), plus the run and dataset IDs for paging the full dataset. Behavior: starts one run of the Apify Actor "scrapemint/stock-earnings-estimates" through Apify's hosted MCP gateway (mcp.apify.com) with your own APIFY_TOKEN; the run uses your Apify account. Read-only: it only reads public web data and changes nothing on the source site. Docs: https://apify.com/scrapemint/stock-earnings-estimates |
| fatihtahta--kalshi-scraperA | Kalshi Scraper | Fast & Reliable. Get live prediction market data from Kalshi.com with tickers, categories, prices, and volume metrics. Fast, reliable, and structured for analysis. Ideal for traders, researchers, and data teams. When to use: Use when you need current Kalshi prediction-market prices, volumes and categories. Returns: the run's dataset rows as structured JSON (one row per result), plus the run and dataset IDs for paging the full dataset. Behavior: starts one run of the Apify Actor "fatihtahta/kalshi-scraper" through Apify's hosted MCP gateway (mcp.apify.com) with your own APIFY_TOKEN; the run uses your Apify account. Read-only: it only reads public web data and changes nothing on the source site. Docs: https://apify.com/fatihtahta/kalshi-scraper |
| parsebird--polymarket-scraperA | Polymarket Leaderboard Scraper. Scrape Polymarket leaderboard rankings with full trader profiles. Extract wallet addresses, usernames, profit/loss, volume, positions, recent trades, bios, and social links. Filter by time range, category, and ranking type. When to use: Use when you need Polymarket leaderboard rankings and trader profiles (profit/loss, volume, positions). Returns: the run's dataset rows as structured JSON (one row per result), plus the run and dataset IDs for paging the full dataset. Behavior: starts one run of the Apify Actor "parsebird/polymarket-scraper" through Apify's hosted MCP gateway (mcp.apify.com) with your own APIFY_TOKEN; the run uses your Apify account. Read-only: it only reads public web data and changes nothing on the source site. Docs: https://apify.com/parsebird/polymarket-scraper |
| ryanclinton--wayback-machine-searchA | Wayback Machine Scraper - Track Website Changes Over Time. Search the Internet Archive's Wayback Machine for historical snapshots of any website. Retrieve archived page metadata -- including timestamps, URLs, MIME types, HTTP status codes, and content hashes -- for up to 10,000 snapshots per run. When to use: Use when you need archived Wayback Machine snapshots of a URL or domain over time, e.g. to see what a page said on a past date. Returns: the run's dataset rows as structured JSON (one row per result), plus the run and dataset IDs for paging the full dataset. Behavior: starts one run of the Apify Actor "ryanclinton/wayback-machine-search" through Apify's hosted MCP gateway (mcp.apify.com) with your own APIFY_TOKEN; the run uses your Apify account. Read-only: it only reads public web data and changes nothing on the source site. Docs: https://apify.com/ryanclinton/wayback-machine-search |
| data_xplorer--google-news-scraper-fastA | Google News Scraper. Scrape Google News in real time, including images and descriptions. This tool extracts complete structured data: high-resolution visuals, full, titles, sources, dates, and direct URLs. When to use: Use when you need recent Google News articles for a query (title, source, date, URL, image). Returns: the run's dataset rows as structured JSON (one row per result), plus the run and dataset IDs for paging the full dataset. Behavior: starts one run of the Apify Actor "data_xplorer/google-news-scraper-fast" through Apify's hosted MCP gateway (mcp.apify.com) with your own APIFY_TOKEN; the run uses your Apify account. Read-only: it only reads public web data and changes nothing on the source site. Docs: https://apify.com/data_xplorer/google-news-scraper-fast |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 7 tools
Each tool targets a distinct data source (institutional calibration, economic calendar, EPS estimates, Kalshi, Polymarket, Wayback, Google News), so misselection risk is low. Minor overlap: Kalshi and Polymarket both return prediction-market pricing, and Wayback/Google News could be confused as generic 'search news/history' utilities in a forecast-accuracy context.
All seven tools follow a uniform 'vendor--actor-slug' convention with descriptive kebab-case suffixes, which is predictable and scannable. It deviates from the verb_noun ideal and the vendor prefixes add noise, but consistency is high.
Seven tools is well-scoped for a curated research bundle, and each contributes a distinct angle on forecast accuracy or its corroborating evidence. No filler or duplicated capabilities.
Core coverage exists (institutional track records, analyst estimate vs actual, prediction-market odds, historical snapshots for verification), but the surface is thin on lifecycle operations like scoring a custom forecast or comparing multiple institutions head-to-head. Wayback and Google News feel like auxiliary gap-fillers rather than completing the stated domain.