Aggregator MCP proxy that collapses N downstream MCP servers into 4 meta-tools with progressive tool discovery, and compresses large tool outputs (HTML→Markdown, JSON summarization) with full-output retrieval via read_more and a per-session token-savings report.
A high-performance MCP server providing up-to-date documentation for Go, npm, Python, Rust, Docker, Kubernetes, Terraform, and more — fetched from official sources, not training data.
MCP server that validates AI-generated 1C:Enterprise (BSL) code against the real platform API. Catches unknown enum values, wrong argument counts, and missing type members by parsing the platform syntax-helper (shcntx_ru.hbk) — independent Rust implementation with built-in expression validator.
An MCP server that records agent execution metrics and exposes a Context Window Explorer to visualize exactly what entered the model's context window across sessions, tokens, and tool calls.
MCP server providing lossless file reads with deduplication, per-repo token metering, and HMAC-signed context receipts. Enables auditable, vendor-neutral measurement of what an AI agent saw.
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.
MCP server that inspects local codebases and generates source-grounded context packs for coding agents, with tools for repository search, symbols, dependencies, Git analysis, and context generation.
Exposes tools for AI assistants to query a persistent SQLite+FTS5 index of C/C++ symbols parsed from real build commands, enabling sub-millisecond lookup, full-text search, and natural-language explanation without hallucination.
Provides redacted access to a private local knowledgebase for coding agents, allowing them to inspect files while hiding sensitive names and identifiers.
This MCP server provides tools to manage, score, compress, and prune AI agent conversation context, helping keep agents focused and reduce token costs. It is a free, local, pure Python solution for any MCP client.
Remote MCP server that exposes context-keeper's rationale store (decisions, pipelines, constraints) over Streamable HTTP, deployable on Cloudflare Workers and usable as a claude.ai custom connector.
An event-driven MCP server that enables agents to share context streams, publish and subscribe to events, manage tasks, and follow protocols, keeping a fleet of agents mutually context-aware in real time.
Enables AI agents to access real-time Windows PC context including active window, system performance, screen time, productivity analytics, and historical usage through MCP tools.