Best Focus AI Skills & MCP Servers

Agent registry — register AI agents with capabilities, list available agents, query capabilities.

Session metrics tracking — token usage, costs, duration, and per-tool statistics.

Persistent key-value memory — store and recall information across sessions as JSON files.

In-memory file cache — avoid redundant disk reads with mtime-based invalidation.

Knowledge base — index documents, search by content, fetch entries, purge stale data, rank by relevance.

Change impact analysis — given a file or symbol, find what files are affected by a change.

Project onboarding workflow — auto-discover project structure, conventions, and key files for a new contributor or AI agent.

Hello-world brick — returns the message it receives. Serves as a smoke test for the FocusMCP pipeline.

Token budget management — estimate and optimize token usage for AI agents.

Knowledge graph export — generate HTML, Mermaid, GraphML, Cypher, Obsidian, and wiki formats.

Composite brick — orchestrates smartread, cache, compress, tokenbudget, and overview to deliver optimal context within a token budget.

Multi-source research — collect info from multiple files/sources, synthesize findings, validate consistency.

Shell command execution — run commands, background processes, kill, and compress output.

API route detection — scan projects for Express, Fastify, Next.js, SvelteKit route definitions.

Write files — create, overwrite, append.

Graph clustering — detect communities, explain groupings, identify architecture layers.

Pack files into a compressed context bundle — reduce token usage by extracting only signatures, maps, or full content.

Task dispatch queue — send tasks, manage queue, cancel, check status for multi-step workflows.

Sandboxed code execution — run JavaScript/TypeScript snippets in an isolated VM context.

AI team coordination — loads dispatch, parallel, debate, review, agent for multi-agent orchestration.

Inline, extract, and move refactoring — inline variables/functions, extract code to new functions, move between files.

Structured decision-making — define options, analyze tradeoffs, recommend, and record decisions.

File access heatmap — track read/write patterns, detect hot and cold files.

Track and report token savings — compare FocusMCP usage vs naive full-read, trend over time, ROI.