MCPSharp is a .NET library that helps you build Model Context Protocol (MCP) servers and clients - the standardized API protocol used by AI assistants and models.

The cloud Mac alone, with Xcode, for AI agents: run commands, build and test, use the screen.

Shared memory for teams and their AI agents: Markdown concepts with typed links in shared bundles.

Memory for your AI: what you saw on screen, said in calls and worked on, searchable by agents.

Persistent memory, knowledge graph, task management and more for AI agents via MCP.

Memory for AI agents: facts a person approved, each with a link, and answers that cite them.

Audit AI agents' tool calls, planning and memory; Base on-chain data; pay per call via x402.

Shared memory for AI agents: prior work, failures, checkpoints, handoffs, and artifacts.

Draft posts in your own voice from saved business context and check every draft before you post.

Shared memory for AI agents: a hierarchical database where totals add up and writes are attributed.

HL7 FHIR R4 health-data API for AI agents: free sandbox, 30 synthetic patients, AI-ready context.

Shared memory and mail for your AI agents. Verified with Claude Code; other MCP clients in testing.

Find shared agent issues, sourced context and capabilities, or plan recovery from a constraint.

OSINT investigations with traceable evidence: domains, URLs, IPs, scams and business records.

Query robotics, drone, and IoT data in plain English through an MCP server, with an intelligent edge data reduction pipeline that keeps only the data that matters.

Core interfaces and reference storage adapters for the ggui MCP server — UiGenerator, GguiSessionStore, BlueprintProvider, AuthAdapter, plus in-memory and SQLite implementations. The pluggable seam layer @ggui-ai/mcp-server is built on.

Team-aware memory: intent, decisions, real-time conflicts for AI coding assistants.

AI-powered spec generation and review using multi-repo code graph intelligence for backend teams that ship to production.

Your product team's shared strategic memory — an MCP server your AI tools reason over.

Plan a huge chunk of work (more than one agent session can hold) as a shared map of decision tickets on your issue tracker, and resolve them one at a time until the way to the destination is clear.

Composable, view-based context for DeepSeek Harness. Pluggable sources and strategies, with layered memory and self-evolving skills out of the box.

Cost tracking for DeepSeek Harness: session and model costs, token usage, budgets, provider balances, and coding-plan quotas. Bilingual English/Chinese UI.

Model Context Protocol for WinDbg.

Helping coding agents never make mistakes working with public or private libraries without wasting the context window.