agent-context

TiDB is built for agentic workloads that grow unpredictably, with ACID guarantees and native support for transactions, analytics, and vector search. No data silos. No noisy neighbors. No infrastructure ceiling.

Autonomous Agents (LLMs) research papers. Updated Daily.

Symbol Delta Ledger (SDL-MCP) is a policy-centered context budget layer for coding agents: Symbol-graph intelligence combined with precision tools. It turns sprawling codebases into compact, high-signal context that saves tokens, speeds up workflows, and improves agent output.

Git-native memory for coding agents. Repo memory before the diff.

Repo-native shared memory for AI coding agents.

Full AI context and content layer for coding agents over one MCP server — tree-sitter code-map, document RAG, shared memory, multi-agent comms, web crawl, git history + blame. 300+ languages, 10+ agent harnesses, pure Rust.

Give your AI agents grounded, reusable career context.

Record meetings and dictation on your Mac. Everything becomes plain Markdown files that Claude, Codex, or any AI can search. Free, open source, 100% local transcription.

Google Drive for AI agents — share files with your team, share context across your agents. Open source, no server required.

Build system for AI coding-agent context. Generate deterministic, explainable context artifacts for Claude, Codex, Cursor, and MCP.

A community-driven specification for creating, validating, and versioning structured context for AI systems

Local-first CLI to read, compare, and hand off sessions across Claude Code, Codex, Gemini, and Cursor agents. Checkpoints, cross-agent messaging, zero npm deps.

Open-source client SDKs (Python, TypeScript, Go), CLI, API docs, and prebuilt binaries for the Mneme agent cognition runtime (memory, context, ontology, knowledge). Apache-2.0.

Workspace for humans and AI agents. Every block is a doc, a task, a discussion, and agent context — one object, not three copies your agent has to choose between. Context is lexically scoped: pin a rule at the root, every task below inherits it. Self-hosted, MCP-native.

CLI + MCP for agent context: a task layer over TickTick, Notion, GitHub, Obsidian & more (RRF retrieval, provenance, reviewed writes, undo) plus a knowledge-graph layer — ats kg: facts from any source, human-ratified. Recommended engines: Graphiti (server), LadybugDB (embedded).

Search all your coding-agent chats, then resume any session in any agent.

Your project remembers across coding agents. Compact, cited project memory for Codex, Claude Code, Cursor, and compatible tools.

Multi-vendor AI coding knowledge base. Auto-synced docs for Claude Code, Cursor, Codex, OpenAI, Gemini. Long-term context for AI agents — clone, open, ask.

Claude skills for evaluating folder architecture and running staged AI workflows, built on the ICM five-layer context hierarchy.

The context layer for AI agents — open, structured, searchable knowledge protocol (Domain → Concept → Link). Skills-first, no MCP server needed.