"Business Intelligence and Research Tools for Sales" matching MCP servers:

Domain-expert SMB sales playbooks for AI agents. Discovery questions, objection handlers, cold email + LinkedIn DM templates, BANT/MEDDIC frameworks, closing tactics. Built by an ex-Criteo (268% quota) / ex-Deel ($12B) / ex-HBO / ex-Bloomberg enterprise AE. Use when your AI SDR needs real human-tested sales artifacts.

Exposes web search and page fetching tools via the MCP protocol, allowing integration with AI editors like Cursor for autonomous research workflows.

Persistent memory for AI agents. Store, recall, and share knowledge across sessions with five MCP tools: remember, recall, context, forget, and share. Includes semantic search and agent/user/org scoping.

Research methods, workflow tools, and independent review for AI agents, packaged as a Skill, plugin, and local MCP server.

Enables autonomous enterprise sales agents to generate customized B2B sales proposals, ROI framing, competitive battlecard talking points, and objection-handling scripts for budget, security, compliance, and migration resistance, along with next-step calls to action.

Enables deep research tasks using a multi-agent architecture that integrates any LLM and MCP tools. Available via MCP stdio, streamable HTTP, and SSE transports.

Enables AI agents to perform workspace file operations (read/write/recover) with transaction-safe guarantees, durable recovery, and explicit human approval via a separate Broker.

Enables agents to execute structured research runbooks against a 440+ tool data bank and receive reports in which every number traces back to a cited source in an evidence ledger. Exposes tools for launching jobs, listing available runbooks, polling run status, and fetching finished markdown or HTML reports.

A local MCP server that enables AI applications like Claude Desktop to securely access and work with Obsidian vaults, providing capabilities for reading notes, executing templates, and performing semantic searches.

Enables AI agents to perform deep web research by searching, fetching, chunking, retrieving, and synthesizing cited answers from exact source passages via a deep_research tool.

Provides image recognition capabilities to Codex/Claude Code by routing 'look at screen/screenshot' requests to a multimodal model via an API relay. Enables UI automation agents to analyze local screenshots and return descriptions or structured JSON coordinates.

Aggregates and routes multiple MCP servers with intelligent tool recommendation and batch parallel execution, enabling unified access and efficient tool usage.

Paid web research MCP tools for autonomous agents: search, page extraction, citations, and diff monitoring through a live x402 API. Unpaid calls return the Base USDC payment requirement so agents can pay and retry safely.

A small local MCP adapter that lets Claude Code delegate bounded research work to Codex plan credits without giving the worker ownership of the final report.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Enables users to create and refine a research outline, queue report generation in the background, and retrieve progress or completed Markdown reports, with automatic checkpointing so unfinished work can resume after a restart.

Evidence linting for AI answers: flag broken references, unmatched quotes/numbers and evidence gaps before human review. Local Python/stdio: 32 tools. Hosted Output Verification has a separate MCP catalog: https://output-verification.agendamcp.dpdns.org/mcp/agent. Start free with a saved synthetic example at https://output-verification.agendamcp.dpdns.org/. No factual-truth certification.

Implements Anthropic's multi-agent research architecture with subagent spawning, adaptive stopping, and citation processing for automated research.

Enables autonomous web research, file management, and dynamic UI dashboard generation through Gemini LLM and FastMCP.

Provides computational tools for systematic reasoning, including boolean evaluation, date arithmetic, object counting, state tracking, and format validation, to enhance agent capabilities and eliminate calculation errors in reasoning tasks.