"Two agents working simultaneously" matching MCP servers:

Exposes Azure AI Foundry agents, workflows, and AI Search vector-database capabilities as MCP tools, enabling natural language interaction with agents, semantic search, and index management.

Pay-per-call USDC payment proxy for AI agents. Issue scoped Pay Tokens with hard spending caps and auto-journal every charge to freee / Money Forward / QuickBooks.

MCP server that integrates sql-sop SQL linter into LLM clients, enabling linting SQL queries and listing lint rules via chat tools.

A governed SQL gateway that exposes typed tools to AI agents, compiling safe read-only queries from a semantic layer while blocking PII before execution, supporting SQL Server, Postgres, and SQLite.

MCP server for the Indico meeting agenda system, enabling AI agents to search event categories, browse agendas, and extract contribution and session details. Works with multiple Indico instances simultaneously.

The open-source, self-organizing memory for all your AI tools. Persistent memory over MCP (remember, recall, observe): background agents extract entities, resolve conflicts, and keep cited syntheses current in an append-only, encrypted, single-tenant vault.

A Python-based MCP server that enables AI agents to query the Microsoft 365 Roadmap programmatically.

Multi-source academic paper search, citation graph exploration, and PDF download as an MCP server, designed for LLM agents doing research.

Startup valuation calculators for AI agents: 14 MCP tools covering 80+ formulas from the Startup Valuation textbook — probability, time value, CAPM, pre-revenue methods (Scorecard, Berkus, VC Method), options, comparables, SaaS, marketplace, fintech, biotech, hardware, international, stakeholder equity, and emerging methods.

Turns team chat (Slack, Discord, MS Teams, Mattermost) into a living knowledge base - a typed knowledge graph plus auto-generated wiki - exposed to AI agents through a 28-tool MCP server with semantic search, expert finding, and decision tracing.

Enables AI agents to send emails and manage tasks in Microsoft To Do with scoped, low-risk access to Microsoft Graph.

A persistent Python REPL MCP server for AI agents with stateful execution, real timeouts, crash isolation, and an MCP bridge to call other tools in the project.

A Model Context Protocol server that provides LLM Agents with a comprehensive toolset for IP geolocation, network diagnostics, system monitoring, cryptographic operations, and QR code generation.

The company registry MCP: company data for AI agents, any country. One MCP server and REST API over national business registries — Norway (Brønnøysundregistrene / Enhetsregisteret, lookup by organisasjonsnummer/orgnr, VAT status) and the United Kingdom (Companies House, lookup by company number, accounts and confirmation-statement deadlines). Five tools: lookup_company, search_company, company_dea

Read-only MCP server for Grafana Loki: lets AI agents (Claude Code, Cursor, Copilot) discover labels, read bounded LogQL pages, count lines by label or time, and export logs — across several Loki stands

Official MCP server for Rendobar. Lets AI agents run serverless media processing and upload local files.

A Model Context Protocol server that gives AI agents real-time access to Excel workbooks in OneDrive, answering natural-language questions with live data. It caches only sheet structure, never cell values, and fetches current ranges via Microsoft Graph for each query.

Enables agents to make calibrated decisions via six MCP tools for classification, relevance ranking, claim verification, action gating, next-step control, and model listing, using Jev's System One model without generating text.

A universal MCP aggregator toolkit that connects AI agents to multiple MCP servers through a single unified configuration. Features ready-made templates, cross-repo prompt workflows, and an npm package for zero-config installation.

An MCP server that protects AI agents and RAG systems from adversarial poisoning attacks like prompt injection, steganography, and data anomalies through multi-layer sanitization, entropy-based detection, and consensus verification.