"SST" matching MCP servers:

Enables AI assistants to transcribe audio files using dTelecom's real-time speech-to-text with pay-per-use USDC micropayments, no API keys required.

Transcribes audio files by referencing them in chat, using OpenAI's speech-to-text models locally without uploading audio, and supports speaker diarization.

Enables AI assistants to manage remote servers via SSH with 43 specialized tools for command execution, file editing, directory operations, and background tasks across Linux, macOS, and Windows.

A Model Context Protocol server that enables querying Bitcoin blockchain data, including address information, transaction details, mempool statistics, and ordinals/runes data through the Satstream API.

MCP server for scraping product prices, offers, reviews, and details from Amazon, Google Shopping, Bol.com, and Coolblue via natural language commands, with spend-cap protections.

Enables distributed agents to synchronize a last-write-wins element set using conflict-free replicated data types, Lamport timestamps, and deterministic two-way state merge over MCP.

Enables AI agents to query governed data warehouses through plain language, returning grounded answers with SQL, confidence grades, and signed receipts while enforcing access, testing, and audit controls.

Provides MCP tools for searching, listing, and retrieving MST developer documentation.

AST-aware TypeScript/JavaScript codebase exploration for AI agents, providing high-precision symbol resolution, reference finding, and structural analysis via MCP tools.

Implements a Model Context Protocol server using Server-Sent Events for real-time communication with OAuth 2.1 integration via Ory Network, enabling secure AI model communication with authentication and client management.

Enables comprehensive TLS security audits for any domain, including certificate validity, expiry warnings, cipher suite weaknesses, deprecated protocols, and HSTS checks. Supports single and bulk domain inspection via MCP tools or a CLI for CI/CD integration.

Enables deterministic, AST-based rewriting of Python imports and callsites, so module paths can be re-aliased and migrated across a codebase without regex errors. It also supports dependency graph auditing and refactoring planning with token-efficient output for coding agents.

Enables static AST-based dataflow analysis to trace untrusted sources to sensitive sinks, supporting automated code review and security auditing through MCP.

Generates fullstack UI component AST patches with Tailwind tokens, enabling AI agents to produce structured UI patch outputs for frameworks like v0 and Lovable.