"Understanding the Purpose of Research" matching MCP servers:

Enables declarative FDTD validation, guarded cloud-task workflows, and normalization of Tidy3D simulation results into metadata and bounded CSV observables, while keeping credentials and cloud-execution privileges isolated.

The server functions as an MCP server to interact with Notion for retrieving and creating survey data, integrating with the Claude Desktop Client for conducting and reviewing surveys.

MCP server that turns operator-authorized local or synthetic source records into auditable research briefs, with every finding linked to exact excerpts and hashes. Exposes a single build_research_brief tool over deterministic, no-network stdio.

Enables local, offline ledger and replay operations for alpha research via five typed stdio tools, allowing status checks, report retrieval, method-card listing, replay execution, and run stopping without exposing live or submission capabilities.

Enables offline-first alpha research by providing a local stdio interface to query run status and reports, list approved method cards, execute replay runs, and stop runs, all without any submission capability.

MCP server that archives Decent DE1 espresso shots from Visualizer.coffee into SQLite and provides analysis tools for shots, beans, and profiles via MCP.

Enables AI agents to inspect schemas, walk Delta table history, run read-only DuckDB queries, and check data-quality and job-run status safely.

Enables AI agents to inspect, query, test, and safely fix dbt projects and BigQuery warehouses under policy-enforced controls, with read-only direct queries and dbt-only allowlisted writes.

Provides tools for managing qualitative research knowledge graphs, enabling structured representation of research projects, participants, interviews, observations, codes, themes, and findings.

Creates compact skeleton representations of large JSON files by preserving structure while truncating string values and deduplicating arrays, helping users understand JSON structure without processing the full data payload.

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.

An MCP server that provides comprehensive market intelligence by analyzing data from both the Apple App Store and Google Play Store, enabling users to research apps, track market trends, study competitors, and understand user feedback across mobile marketplaces.

A server that provides tools and utilities to support the implementation of Jij Modeling, featuring easy configuration and an extensible architecture for custom modeling workflows.

Enables structured document understanding of local PDFs via a dual-extract MCP server, combining MinerU text/layout and Qwen3-VL vision with fusion adjudication for field extraction, tables, formulas, and validation. Fully local and offline.

Enables LLMs to retrieve, analyze, and visualize stock prices and financial report data for quantitative trading research and investment analysis. Provides real-time and historical stock data, financial statement analysis, key metric calculations, and trading signal visualization.

Enables natural language management of Apache Airflow workflows, including DAG monitoring, task control, and configuration, via the Model Context Protocol.

Connects MCP clients to databases like Snowflake, BigQuery, and Databricks through Alkemi's data platform, enabling natural language database queries with proper schema understanding and metadata management for consistent team-wide access.

Let LLMs analyze sensitive data safely by querying a tokenized, join-preserving copy of the database, with fail-closed PII scanning and provable numeric equivalence.

Enables assistants to reach a local market-research lab over MCP, including provenance-tagged market snapshots, falsifiable theses with invalidation rules, strategy backtesting with overfitting checks, committee reviews, portfolio analysis, and report export.

Bridges the Model Context Protocol to the Tabular Object Model, enabling natural language inspection, optimization, and authoring of DAX in Power BI Desktop.