"A resource for understanding Claude's context window and capabilities" matching MCP servers:

Provides an external context buffer so a local model can maintain session memory across long tasks and search and page through large documents without loading them whole into its limited context window.

A minimal MCP server that exposes Gemini's web and multimodal understanding (video, audio, document, image) through five dedicated tools.

Enables AI agents to maintain persistent, inspectable understanding through typed, revisable updates, and to coordinate multi-agent work via shared graph-based stigmergy.

Enables local video inspection and offline transcription with timestamped JSON and Markdown output, enforced filesystem boundaries, and reproducible content-addressed caching.

Enables LLMs to read and write local user data, generate fake users via sampling, and interact with structured prompts and resources.

An MCP server for searching, browsing, and downloading game sprites, models, textures, and sounds from The VG Resource network, covering 100k+ assets across 50+ consoles.

Serves read-mostly MCP tools across ten mock verticals and investment use cases, each backed by bundled SQLite databases, with optional proxying of investment tools to a user-supplied banking API. It enables clients to query realistic vertical data through OAuth-protected MCP endpoints over HTTP or WebSocket.

Enables users to look up public company earnings dates and reporting windows by providing identifiers like ticker, domain, or CIK. It returns fiscal year end, next reporting date, and an outreach window, helping plan investor communications.

License-aware game development resource discovery MCP server. Helps AI coding agents find reusable game assets with commercial-use filtering, license classification, and attribution generation.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

A Model Context Protocol server for querying and analyzing Azure resources at scale using Azure Resource Graph, enabling AI assistants to explore and monitor Azure infrastructure.

Enables governed Codex work sessions by planning bounded segments, maintaining capacity reserves, and creating checkpoint-based resume contracts so long-running jobs can pause and resume deterministically within quota limits.

Minimal MCP server for testing client support for resources/subscribe and notifications/resources/updated, simulating an asynchronous status update.

Enables querying a live Satisfactory game through Ficsit Remote Monitoring to answer questions about production, power, logistics, and factory health.

Enables AI clients to read and write to a user-owned markdown bucket via S3-compatible storage, providing a persistent shared context layer across different AI tools.

Local-first documentation for AI agents

An MCP server that keeps raw tool output out of the context window by sandboxing and compressing results (about 98% reduction), persisting file edits, git operations, tasks and decisions in SQLite with BM25 retrieval so the agent resumes after compaction, and enforcing routing across 17 platforms via MCP and hooks. It also encourages the model to write scripts that compute answers and log only results instead of reading large data into context.

An MCP server that preserves LLM context by intercepting large data outputs and returning only concise summaries or relevant sections. It enables efficient sandboxed code execution, file processing, and documentation indexing across multiple programming languages and authenticated CLIs.

Provides AI assistants with real-time visibility into your codebase's internal libraries, team patterns, naming conventions, and usage frequencies to generate code that matches your team's actual practices.

MCP server providing deep PostgreSQL context to AI assistants, including schema DDL, index health, foreign key associations, query execution plans, and performance statistics via read-only tools.