An MCP server serving a curated corpus of thinking techniques for AI agents, with tools to classify intents, find and apply techniques, and verify their effectiveness.
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.
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.
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
Intelligent context manager for AI coding assistants that uses a three-level memory system (core, active, archive) to remember project context across conversations.
A plugin that intercepts large MCP tool outputs, indexes them into a local FTS5 knowledge base, and replaces them with summaries, enabling searchable retrieval to save context window space.
A local MCP server that acts as a policy-based firewall for personal context, letting users control agent access to their data with deny-by-default rules, per-field grants, and an audit trail.
An open-source memory layer that provides persistent project context and architectural history for AI development tools across multiple platforms and sessions. It enables AI assistants to maintain a shared understanding of codebases while integrating directly with services like Notion for documentation management.
Claude Context is an MCP plugin that adds semantic code search to Claude Code and other AI coding agents, giving them deep context from your entire codebase.
Aggregates your digital footprint (GitHub, blogs, resume) into a single AI-readable profile and exposes it via MCP tools so AI agents can query your context live.
Enables Claude to index and retrieve context from codebases using self-hosted Milvus for semantic search, with hardened reliability and security for production use.
A local, provider-neutral MCP server for repository-scoped issue handling. It provides a guarded interface to Linear, GitHub Issues, GitHub Projects v2, and Jira Cloud, with preview/apply safety and host-local configuration.
A persistent memory and context management system for AI CLI tools that utilizes a three-layer architecture and semantic search to prevent context loss between sessions. It provides time-aware orientation and smart memory routing to help AI agents maintain project knowledge and architectural decisions.
MCP server enabling AI agents to interact with OpenProject API v3 for project management, including creating and managing work packages, projects, comments, time entries, boards, and user dashboards.