"Analyzing the Stock Market for Investment Opportunities" matching MCP connectors:
GET /v1/connectors — MCP directory API referenceMatching Connector Tools:
The first low-latency wire service purpose-built for AI agents. Ingests 54+ public APIs and 71k RSS feeds across 232 countries, outputs CWF (Cognitive Wire Format) – 80% shorter than JSON, sub-second WebSocket delivery. 9 MCP tools: get_latest_signals, search_signals, get_fused_signal, scope_signals, get_facet_manifest, list_facets, get_related_signals, list_data_sources, get_billing_profile. 26 citable fusion products with verifiable formulas – no black-box scores.
Unstructured document processing for LLM pipelines. Upload as PDF/DOCX/TXT any supported files, extract structured data (PII-redacted), build LLM-ready datasets, and search/export results — all via MCP tools (document.process, job.status, job.result, dataset.build, dataset.search, dataset.export).
Formula-backed WorkPaper tools for workbook readback, input edits, and JSON persistence.
The financial MCP for AI agents - 90+ financial tables, SEC filings, signals, alt-data.
Structured analysis API and remote MCP tool for text, JSON records and numeric series.
Five deterministic micro-tools for AI-agent data pipelines: clean, dedupe, normalize, score, detect.
Evidence-backed public business research for agents with compact, pageable output.
Seven tools over the tabnas parsing engine: parse, validate, diagnose, fixtures, compare.
Ask Personio Recruiting the recruiting-ops questions dashboards miss by connecting applications, stage transitions, candidates, recruiting jobs, categories, org units, workplaces, jobs catalog, webhooks, event activity, and intake documents. Find stage-movement stalls, candidate freshness gaps, source quality by job/category, hiring load by department and workplace, webhook delivery issues, intake readiness gaps, and bottleneck owners. No dashboard build. No SQL.
Multi-tenant FastMCP server for Charles Schwab brokerage data, monetized via DPYC Tollbooth
Connect your Nubank account to AI via Brazil's Open Finance: balances, statements, cards, investment
Token-bounded (< 1.5 KB / ~300 tokens) public data refinery for AI agents. Delivers sub-5ms corporate filings (US SEC EDGAR, UK Companies House, France INPI), beneficial ownership graphs, public procurement tenders (Spain PLACSP, EU TED), and automated corporate risk scoring. Cuts LLM context waste by ~95%.
Paste-your-data analytics over MCP, computed in code: csv_profile profiles columns and data quality, ab_test runs two-proportion z-tests, correlation and growth_rates cover the basics, with funnel_report, cohort_retention, and forecast_trend in the premium tier. No uploads, no external calls, no data retention.
Converts customer-supplied PDF bank statements into checked Excel, CSV, or JSON with balance validation. Hosted Streamable HTTP endpoint; each user brings their own MainBook API key, and the server never connects to bank accounts.
Deterministic company, entity and location lookups for agents - per call, x402 or API key.
Counts and firmographics for 7.5M+ verified US B2B businesses, by industry, state and city.
Pre-computed market data that improves agent reasoning, reduces token usage, and replaces pipelines.
Company-specific regulatory assessments for concrete business questions, as structured data or PDF.
Baking unit conversion (cups/grams/temp/recipe scaling). convert_amount, convert_temperature
A high-performance, edge-native Data Refinery Engine built on Cloudflare's serverless AI stack (Workers, Workers AI, D1, KV, Vectorize) designed to continuously ingest unstructured data, refine it into pristine machine-readable structured intelligence, compute semantic diffs, and serve it directly to AI agents via the Model Context Protocol (MCP) and REST APIs.
