Context Ontology Accelerator

Context is Automattic's internal MCP server for rapidly adding tooling sets with governance and observability layers. It is used in the company's AI-enablement programs, which cover MCPs, shared skills, hooks, and autonomous agents.

Context Mode is an MCP server and plugin for AI coding agents that reduces context-window usage by routing large tool outputs through sandboxed subprocesses. Its execution tools run code in supported languages, process files, fetch and analyze URLs, and return selected stdout or search results instead of exposing raw logs, snapshots, API responses, or file contents to the conversation. The project reports up to 98% context reduction in its benchmarks. It also provides session continuity across supported agents. Hooks capture tool calls, edits, prompts, decisions, errors, and other session events in SQLite; before compaction, the system builds a prioritized resume snapshot, and after compaction or session resumption it retrieves relevant events through SQLite FTS5 search with BM25 ranking. Content indexing uses heading-aware chunking, stemming, trigram matching, reciprocal-rank fusion, proximity reranking, fuzzy correction, and smart snippets. The MCP interface includes execution, batching, indexing, search, fetching, statistics, diagnostics, upgrade, and purge tools. Context Mode supports multiple coding-agent platforms through MCP servers, native plugins, and platform-specific hooks, with automatic routing enforcement where hooks are available and instruction files for platforms without them. The repository states that processing and SQLite storage are local, with no account or telemetry requirement. It is licensed under the Elastic License 2.0, which permits use, modification, and distribution but restricts offering the software as a hosted or managed service and removing licensing notices.

Model Context Protocol (MCP) is an open, standardized protocol layer for connecting large language models and AI agents with external data sources, hosted infrastructure tools, and other contextual data. It defines formats, metadata, protocol schemas, and APIs for sharing information and tools, attaching, referencing, and validating context such as documents, embeddings, and provenance, while supporting scoped authentication and permissions. MCP translates JSON requests from an agent into calls to service APIs, including CRM, container-management, and GKE capabilities, and can provide design-system context and related tools for generating consistent applications. The official project publishes its specification, documentation, and protocol schema; the schema is defined first in TypeScript and also provided as JSON Schema for broader compatibility. The protocol was created by David Soria Parra and Justin Spahr-Summers, is hosted at modelcontextprotocol.io, and is licensed under the MIT License.

MyContext is a local-first desktop app from openTrinity that builds a private personal work-context layer from sources such as instant-messaging conversations, documents, and meeting records. It stores local copies, indexes, source references, and derived context in an on-disk SQLite vault, then organizes them into a personal context graph linking people, projects, topics, events, conversations, and supporting facts. Its search and answer workflow combines local full-text search, semantic retrieval, and graph queries, with agents assembling answers from traceable source material and falling back to ranked local results when the agent runtime is unavailable. A digital-self workflow recalls relationship-specific context and communication history to draft replies, while sending, deletion, and other consequential actions require explicit user confirmation. The repository describes an Electron and React desktop architecture with source connectors, incremental ingestion, context processing, retrieval, knowledge-graph, persona, and isolated agent-runtime layers. MyContext is in developer preview and under active development; its README warns of compatibility-breaking changes and migrations that may require recollection. It is licensed under the Elastic License 2.0, which permits use, modification, and self-hosting but restricts offering it as a hosted or managed service to third parties.

A preview Amazon Web Services service that lets AI agents discover and access data across Aurora, Amazon S3, and other AWS data stores through a unified context layer.