"Cloud Infrastructure Management and Deployment Tools for Oracle Cloud and A2A Communication" matching MCP servers:

MCP server for Aspose PDF Cloud, enabling PDF storage, conversion, and extraction operations (merge, split, text/table/image extraction) via CLI and MCP.

MCP server for the air-Q Cloud API, enabling remote retrieval of air quality sensor data and historical analysis through read-only tools like listing devices, fetching readings, and exporting charts or data.

A hosted Model Context Protocol server that connects AI agents to a project-scoped growth workspace, exposing tools for project knowledge, analytics, research, planning, media generation, drama intelligence, and skill sync.

Detects whether a company runs cold email outbound and identifies the email sending infrastructure, including sending domains, platforms, and authentication status.

A local, read-only MCP server (plus CLI) over your own stock/ETF transaction log. A deterministic core computes drawdown-first risk with bootstrap confidence intervals and validates targets with walk-forward verdicts. The assistant narrates, but the number fence makes it structurally impossible for the model to produce a figure.

Accurate astronomical catalog data and observing session planner for LLM assistants. Stops hallucinated magnitudes, coordinates, and visibility.

3D printing filament and materials knowledge MCP server. Gives LLMs authoritative access to 7,000+ filaments and curated material science knowledge.

An MCP-native pipeline for collecting structured intelligence on higher education institutions using the WHED schema, enabling scraping, extraction, validation, and saving of profiles.

Fuses five market signals into a five-state regime classifier to determine market conditions and recommend trading postures for risk management.

Give AI agents cited funding, money-market, FX and capital-market evidence through 16 public MCP tools. Keep source dates, freshness checks and coverage gaps attached; China macro coverage is metadata-only. No API key is required for the public surface. Research context only; no trade execution.

Enables researchers to turn property-history questions into reviewable evidence dossiers by gathering sources, tracing people and places, linking conclusions to supporting or opposing passages, and exporting portable backups.

MCP server for Jupyter notebook navigation and editing. Reads .ipynb files directly as JSON, providing efficient tools for reading, searching, and modifying cells without needing a Jupyter server.

Presents a plausible, tool-rich workspace surface — file reading, credential listing, command execution, database queries, and configuration retrieval — that returns only synthetic results while logging every connection, tool call, and argument received. It enables researchers to measure what MCP clients and agents actually do when handed dangerous-sounding tools, including whether they follow injected instructions or complete a retrieve-then-use credential chain.

Enables Codex to control a Gephi 3D network view through natural language, including network generation, 3D layout, node focus and neighbor highlighting, layered views, and PNG/PDF export.

Enables users to describe a project in an MCP client and work through pre-submission grant phases, including finding fitting programs, checking eligibility and blockers, pulling precedent from past awards, shortlisting, and drafting memos, budgets, and submission checklists. Coverage is full for US grants and partial (discovery and precedent only) for Canada, with no win-odds estimates or post-award reporting.

Provides five rigorous reasoning protocols (debate, red team, audit_argument, threat_model, check_study) that run on the AI you're already using, requiring no extra API keys or costs.

Provides tools for AI-powered graph analysis, including relationship extraction, adjacency matrix creation, and network centrality calculations. It enables users to perform complex structural analysis and generate interactive D3.js visualizations from structured data.

Enables users to preprocess, analyze, and visualize CSV data through comprehensive tools for data manipulation, statistical analysis, and graph generation.

CNN's Fear & Greed index for the US stock market: current score and rating, the seven component indicators, and about a year of daily history. Go standard library only, no API key required.

Scholarly integrity and papers — citation checks, literature/PubMed search, academic experts, PDF tables (6 MCP tools).

Classifies company sites as B2B or B2C and as SaaS, online store, agency, manufacturer, wholesaler, distributor, or marketplace, while matching your own buyer phrases and returning the quoted text and page as evidence. Runs deterministically on Apify, giving one row per domain with grace-free status rows for unreachable, blocked, or empty sites.

Public leads and enrichment — NPI, podcasts, local businesses, hiring, websites, teams, trends, trucking (8 MCP tools).

Deterministic US equity-compensation tax optimizer. Six tools cover ISO/AMT exercise scheduling, NSO sell-vs-hold, RSU vest-and-sell, single-stock concentration, protective put / zero-cost collar pricing, and Section 1202 QSBS qualification. Federal plus 50-state plus DC tax math.

One-call Australian health and welfare data plumbing via AIHW — cited responses for practical analysis, not a data broker.

Given a company domain or name, it checks ten app marketplaces — HubSpot, Salesforce AppExchange, Slack, Zapier, Shopify, Atlassian, Chrome Web Store, Microsoft, Google Workspace, and WordPress — to report where the company is listed, with each listing's URL, installs, rating, review count, and match confidence. Useful for competitive research and partner-ecosystem audits across many domains in a single run.

Enables users to pull portfolio company lists from Y Combinator, a16z, Sequoia, Accel, and other investors or any portfolio page URL, returning one row per company with name, domain, website, description, and stage or batch. Runs on Apify and produces Clay-ready output, with YC results filterable by batch, industry, region, status, and search terms.

Institutional-grade quantitative stock analysis and research signals for AI agents via the Model Context Protocol (MCP).

Provides actionable financial intelligence tools for AI agents including insider buying signals, earnings IV plays, market pulse, stock analysis, and options strategies via free public data sources.

Enables local literature workflows by searching arXiv, retrieving paper metadata, downloading and parsing PDFs, and retrieving page-cited body evidence for Q&A. It also exposes usage resources and templates for searching, analyzing, and summarizing papers via stdio MCP.

An MCP server for managing pandoc/CSL-YAML bibliographies and verifying citations in documents.