"General context or information search" matching MCP servers:

Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.

MCP server that provides OpenRouter model pricing data, enabling price lookups, trending/cheapest lists, and model searches without an API key.

Provides current weather information for any location and generates AI-powered responses using Google Gemini through FastMCP.

Proxy for OpenAI-compatible backends that compacts conversation history before the context window fills, with read-only MCP tools to search and read back the archived originals.

MCP server that cuts cloud LLM costs 36-42% by indexing context locally and giving agents precision retrieval tools instead of raw context dumps.

Enables agents to find lines in local text files by meaning rather than exact keywords, judging each nonblank line against a natural-language intent and returning scores for every line. It complements lexical search by running locally over stdio and calling a hosted model for the semantic comparison.

Long AI conversations fail in predictable ways. Context-First fixes all four: Failure Mode What Goes Wrong Context-First Solution Context Drift AI forgets earlier decisions and intent as the conversation grows context_loop + detect_drift continuously re-anchor every turn Silent Contradiction New inputs silently overrule established facts — the AI doesn't notice detect_conflicts compares every inp

Enables any calling model to search public X content through Grok's native search using an existing local OAuth login, returning summaries, structured posts, source URLs, and search counts while sharing cached and concurrent searches across local terminals.

Imports private ChatGPT conversations into MCP clients like Codex and Claude Code. Provides tools to fetch remote conversation content and serve cached context via local stdio.

MCP server providing virtual memory for AI context with durable SQLite storage, retrieval, and bounded prompt assembly to manage context windows.

A context window optimizer and session rotator MCP server for agentic workflows that prevents LLMs from running out of context by compacting chat history and rotating sessions.

Enables Codex to run durable, context-bounded image generation and inspection jobs through local MCP tools, returning compact text results, hashes, relative references, and Job IDs instead of media bytes.

Enables AI assistants to search the web using Google Search via Gemini grounding, returning a summarized answer with inline citations and a list of source URLs.

Provides LLMs with persistent memory and reusable skills via MCP, enabling semantic storage and retrieval of user preferences, project context, and step-by-step procedures across conversations.

A daily feed of AI releases, tools and techniques, each with a verification status, source trust score and evidence links. Read-only MCP server, no sign-in or keys.

Enables text-only coding models to read images, PDFs, presentations, spreadsheets, and other non-text files through a single analyze_media tool, combining local document extraction, OCR, and optional vision models with clear evidence labeling.

Enables Codex to run context-bounded image generation and inspection as durable local jobs, returning bounded text handoffs, hashes, relative references, and Job IDs while keeping provider-returned media bytes outside the MCP boundary.

Enables AI coding agents to retrieve the exact original tool-output slices omitted during lossless context compression, via on-demand expansion of hashed references stored in a shared cross-process SQLite vault. Tracks expansion overhead so agents and users can measure true net token savings across debugging sessions.

A durable local MCP server that runs image generation and inspection as persisted jobs, keeping provider-returned media bytes behind the MCP boundary while returning only bounded text handoffs, hashes, relative references, and Job IDs. This keeps image-heavy Codex workflows context-bounded, idempotent, and resumable, with offline mock or optional OpenAI providers.

Enables offline, read-only forensic analysis of Claude Code session transcripts, providing exact token usage, cost estimates, context growth, and compaction suggestions.

Enables MCP clients to perform X/Grok searches through xAI's server-side search tool using the Responses API, returning upstream results without rewriting.

Enables AI clients to run local semantic search over your own documents and code in Chinese or English, with embeddings computed on an Intel NPU. Also lets clients check index status and trigger reindexing.

MCP server that integrates Google's Gemini 2.5 Pro with real-time Google Search grounding for current information retrieval.

Enables Claude to offload code generation to Google's Gemini, saving tokens by writing files directly to disk without returning the content to the chat.

Enables Codex to run context-bounded image generation and inspection as durable local jobs, returning only bounded text handoffs, hashes, relative references, and job IDs while keeping media bytes behind the MCP boundary.

Enables AI agents like Claude and Cursor to query codebases using Augment's context engine via the Auggie CLI.

A Model Context Protocol server that uses Google Vertex AI and Gemini 3.5 Flash to perform deep research with high thinking capability and live Google Search grounding, enabling intelligent, multi-source research via a single tool.

Enables Codex to run image generation and inspection as durable, idempotent local jobs that return only bounded text handoffs, hashes, relative references, and Job IDs while keeping provider media bytes behind the MCP boundary. This keeps image-heavy workflows context-bounded, restart-safe, and resumable across multiple concurrent Codex tasks.

Paid hosted MCP server for OpenAI Codex context compression, providing tools to compress context, estimate savings, issue receipts, and read history.

Enables Codex to run image generation and inspection as durable, context-bounded local jobs, returning only bounded text handoffs, hashes, relative references, and Job IDs while keeping provider media bytes outside the public MCP boundary.