"GNOME Terminal" matching MCP servers:

Enables querying and analysis of container terminal operations including vessel tracking, crane management, and productivity metrics through natural language interactions with a MySQL database.

Enables semantic search of shell session history, matching natural-language intents to past CLI commands, including Warp sessions, for fast keyboard-first command discovery and reuse.

An MCP server that provides web_search and web_fetch tools returning plain text via the tbro terminal browser to reduce token usage, with the trade-off of no JavaScript support.

Provides local agent capabilities for LM Studio including file I/O, terminal execution, and web search.

Enables AI agents to search and browse a curated directory of AI projects, including MCP servers, CLI tools, libraries, and APIs, and submit new projects directly from the terminal.

Web search, page fetching, and research from the terminal or any MCP client — no API key required.

A comprehensive website crawler and SEO analyzer that stores site data in a local SQLite database for AI-driven auditing. It enables users to detect technical SEO issues, broken links, and security vulnerabilities through natural language queries or terminal commands.

Read Google Search Console analytics, inspect indexed URLs, and monitor sitemaps from your terminal or AI agent.

Enables agents to search six clinical-trial channels (global registries, Chinese registries, CDE drug-trial data, and offline snapshots) through one sealed endpoint, merging results only on confirmed registration identity and returning per-source terminal states, coverage caveats, and data cutoffs. This ensures a missing or empty answer can never be silently mistaken for proof that no trial exists.

Enables Claude to search past coding transcripts stored locally — by exact words or by meaning — read them page by page, and reopen them in a terminal to resume work in the original directory. Everything stays on the machine, with a year-long archive.

Lets MCP-compatible clients and coding agents search, list, filter, and retrieve details from a curated catalog of 378 AI agent frameworks, developer tools, and automation repositories using natural language, with bilingual (English/Georgian) descriptions and category, language, and result-limit options. The same catalog is also reachable from the terminal via an accompanying command-line interface.

Enables natural-language search, listing, and retrieval of 378 curated AI agent, developer-tool, and automation repositories directly from Claude Code, Cursor, Codex, or any MCP-compatible client, returning matching repos with Georgian descriptions. Supports category filtering, result limits, and bilingual (English/Georgian) responses, with an equivalent aipulse CLI for terminal use without an MCP client.

Enables MCP clients and a terminal CLI to run web searches through a user's own SearXNG instance, saving every query as a reusable session and optionally generating AI-synthesized answers.

Enables AI agents to share persistent, searchable memory across sessions by ingesting and organizing knowledge from sources like Obsidian, code, transcripts, and terminal sessions. It provides token-optimized retrieval, semantic and keyword search, and MCP/REST access so agents can capture, classify, synthesize, and reuse context.

Provides web search functionality for the Gemini Terminal Agent, handling concurrent requests and content extraction to deliver real-time information from the web.

Enables read-only code search in a specified local directory and public web search through the user's own Devin session, with login handled only in the terminal.

Enables querying Google Search Console data, Core Web Vitals, and PageSpeed insights from the terminal or via MCP tools.

Enables AI agents to share persistent memory by ingesting knowledge from sources like Obsidian, code, documents, web clips, and terminal sessions, then providing token-optimized search, context, classification, synthesis, and capture tools through MCP and REST APIs.

Enables AI agents to capture, classify, synthesize, and retrieve persistent knowledge through MCP and REST APIs, so multiple agents can share memory and improve across sessions. It provides full-text, semantic, and hybrid search with token-optimized context retrieval from sources like Obsidian, code, transcripts, and terminal sessions.

Enables AI agents and terminal users to pull Google's own search-demand figures—monthly volume, 24-month history, true year-over-year, seasonality, competition and top-of-page bid ranges—for keywords they name or discover from seeds, a page URL or a whole site, plus place-name geotargeting. It is strictly read-only, never creating campaigns or spending money, and keeps "no data" distinct from zero searches.