"How to interact with Excel files" matching MCP servers:

Enables AI agents to discover and interact with Proxenio's verified intent network for professional matching, including viewing matches and accepting introductions.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Enables structured, iterative reasoning for complex problem-solving with features like confidence tracking, revision mechanisms, and branching support. Provides flexible validation and multiple output formats for systematic analysis and decision-making tasks.

Enables Codex to delegate coding tasks to an OpenCode CLI locally, returning structured results such as exit codes, session summaries, tool calls, and git diffs.

MCP server that lets you drive Claude Code sessions hands-free by voice from any MCP client, enabling remote models to send prompts, monitor progress, and get results read back.

Reduces Claude's context window costs by automatically summarizing inactive files to their public interfaces using AST parsing, keeping only the full contents of the currently active file.

Enables routing tasks to the right specialist agents, assembling the needed context from a layered catalog of agents, skills, knowledge, runbooks, topics, tools, and connectors, while remembering how a business wants work done.

Teach any AI agent how you use an MCP server – Soft-Landing to your AI integrations

Gracefully closes Cursor work sessions by syncing context files across multiple AI assistants, updating Agent OS files, and automatically committing changes to git with descriptive messages.

Build -> See -> Interact -> Debug over native GUI apps.

Enables learning how to build and use an MCP server with tools, resources, and prompts through a Python example.

A Model Context Protocol (MCP) server that enables AI assistants to perform comprehensive file operations including finding, reading, writing, editing, searching, moving, and copying files with security validations.

An autonomous MCP server that uses the Claude Code CLI to solve coding problems without permission prompts.

One-pass agentic inbox triage as an MCP server: fetch unread Gmail → classify (action_needed/fyi/newsletter/noise) → summarize → extract tasks → draft replies as Gmail DRAFTS (never sends) → flag calendar → write a triage report. Four stdio tools (fetch_emails, save_gmail_draft, append_tasks, write_report); the host is the LLM, so it runs keyless in Claude Code. Gmail scopes: readonly + compose

Enables Claude to interact with Okta's user management system, providing capabilities to retrieve user details, list users with filtering options, and manage user groups.

Provides 14 MCP tools for AI agent infrastructure, enabling knowledge base queries, skill search, handoffs, blueprint validation, trust scoring, identity verification, SLA validation, and compliance checks.

An MCP server that enables LLMs to interact with Agent-to-Agent (A2A) protocol compatible agents, allowing for sending messages, tracking tasks, and receiving streaming responses.

An educational implementation of a Model Context Protocol server that demonstrates how to build a functional MCP server for integrating with various LLM clients like Claude Desktop.

An MCP server integration that enables Cursor AI to communicate with Figma, allowing users to read designs and modify them programmatically through natural language commands.

Enables users to control the cursor in Figma through verbal commands using an agentic AI agent, streamlining the design process with a new interaction method.