"Agent Creation and Orchestration" matching MCP servers:

Give your AI agent the entire China A-share market: 55 datasets of prices, financials, capital flows, corporate events and futures/options, stored locally and queryable with read-only SQL. Built point-in-time with delisted stocks kept, so backtests don't lie — no account, no API key.

Enables users to convert a vendor partner directory (such as PartnerPage or the Shopify Partner Directory) or a trade body member list into one company row per listing, each carrying website, domain, tier, tags, and location for Clay-ready output. It runs the extraction on Apify, returning dataset rows for up to 20 directory URLs with optional deduping, detail enrichment, and a cost cap.

An enterprise-grade data analysis system that enables users to discover data sources, configure analyses, and execute workflows through Claude Desktop. It features intelligent caching, session isolation, and secure JWT authentication for streamlined multi-user data orchestration.

Enables AI agents to discover and query enterprise knowledge documents and business metrics through standardized MCP tools, supporting retrieval, structured sales/order analysis, anomaly scanning, and data lineage lookups.

An MCP server that allows users to interact with YNAB data, enabling access to account balances, transactions, and the creation of new transactions through the Model Context Protocol.

Enables autonomous agents and scraping pipelines to deduplicate high-throughput event streams, repair and validate gigabyte-scale JSONL data, retry HTTP/S requests with exponential backoff and header rotation, mimic Chrome/Safari TLS fingerprints, and sync cross-domain cookie sessions. Tool invocations are metered through x402 USDC micropayments on Base L2, returning a payment challenge until a signed transaction unlocks execution.

Enables AI agents to search data sellers and datasets across categories, inspect sellers and data points, and request purchases, samples, or unlisted data without an API key.

An MCP server that exposes Estuary Flow pipeline operations as typed tools, enabling agents to inspect pipeline health, publish captures and materializations, edit/restart tasks, and read landed documents via tool calls.

Enables natural language interaction with JSON files, providing tools to load, query, aggregate, transform, and export data directly from AI editors.

AI-native service orchestration platform. Discover MCP services by capability, chain multi-service-workflows at runtime, and authenticate per-user via JWKS/External OAuth. A single pAIchart MCP server needs only 10 tools to access hundreds of registered local or network MCP servers solving the context issue individual MCP server tools impose. Enabled by pAIchart's service_call innovation.

Enables AI assistants to manage a GBIF IPT from resource creation to publication, including metadata editing, data validation, Darwin Core mapping, and publishing, through plain language requests.

A tool for SHACL-based assessment, comparison, and coverage analysis of digital passport data models, designed for AI-agent orchestration.

Enables AI assistants to perform MLOps workflows such as experiment tracking, model registry, dataset management, pipeline orchestration, and data lineage by wrapping DVC, MLflow, and Git.

Connects AI clients to the Matih data platform, enabling SQL queries, table profiling, analytics, chart creation, and file uploads through MCP tools with OAuth/PKCE authentication.

Bring professional data to the AI you already use. QVeris connects AI assistants and workflows to services for company financials, social media, life sciences, research, patents, and e-commerce. Discover services, review scope and pricing, call them, and audit usage through one MCP connection. Requires a QVeris API key; charges depend on the selected service.

Enables managing orchestration workflows through tools for creating, preflighting, linting, and running sequences, checking instance status and outputs, sending signals, retrying instances, and inspecting DLQ and usage.

Enables agent tools to validate queries, assess token costs, and extract structured datasets from unstructured text using multiple LLM providers.

Provides deterministic tools for transforming, formatting, and inspecting structured data for AI agents.

Enables AI assistants and editors to profile, clean, and analyze messy CSV/Excel files directly through MCP tools such as profile_dataset, clean_dataset, and list_sheets.

Enables agents to answer analytics questions with provable correctness by resolving metrics through the semantic layer, tracing lineage, traversing knowledge graphs, checking freshness, and searching glossary definitions, while enforcing access controls and logging every call.