"How to query data in Snowflake" matching MCP servers:

Enables AI chat sessions to exchange messages and structured data with each other, preserving provenance and conversation threads, so work in one chat can be reused in another without manual copying.

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.

Every agent action is recorded in a SHA-256 hash chain. Prove to clients that your agent did what it said it did. Record, query, verify, and export agent activity.

Enables agents to query the TypeSafe Jev decision model for typed answers—yes/no, choice, and score questions—with calibrated probabilities, batched in a single request under a local context-budget guard.

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.

I built this local stdio MCP adapter to discover, preview, and purchase live agent data APIs, including vendor risk, company intelligence, transaction preflight, and EVM reads. Free discovery and previews require no wallet. Optional paid calls settle in Base USDC through x402 v2; auto-pay is disabled by default.

An MCP relay that adds a use_jev tool to every connected server, letting the Jev model autonomously select and execute tool calls while the calling model supplies any required text values. It enables agents to delegate multi-step tool use across all configured MCP servers through a single unified interface.

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.

Enables MCP clients to access the full Interactive Brokers TWS API—contracts, market data, history, scanners, news, fundamentals, account/P&L, and orders protected by safety rails—through an IB Gateway.

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

Enables two-model orchestration where Gemini in Google Antigravity delegates coding tasks to Qwen 3.8 Max in Qwen Studio Desktop via CDP, managing prompt delivery, file generation, continuation, and verification.

Enables AI agents to record and query reasoning steps in SQLite, offloading trace data from the context window, with DAG support and persistent cross-session memory.

Enables AI agents to publish posts, images, comments, and reactions to LinkedIn as the authenticated user, with built-in safety features like daily budgets and deduplication.

Enables AI assistants like Claude to interact with humans through intuitive GUI dialogs, supporting text input, choices, confirmations, and information displays.

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

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

A task-level STDIO MCP server that lets Codex or any other MCP client hand off scoped coding jobs to an asynchronous worker agent which reads the code, edits files, and runs tests, while the client keeps ownership of planning and acceptance. Exposes submit, wait, query, follow-up, and cancel tools so multiple clients can queue and monitor tasks against a chosen project root.

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.