ProtoMap

Cap'n Proto is a binary data interchange format, interface definition language, and capability-based RPC system developed around core tools and a C++ library. Its generated code lets programs in multiple languages read a shared memory layout without an additional serialization step, and it provides RPC capabilities for communicating between components. The project describes itself as a binary alternative to JSON and as a faster alternative to Protocol Buffers; the repository contains the development branch and warns that it may include breaking API changes.

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.

Repowise is an open-source, self-hosted codebase-intelligence tool for developers and coding agents. It builds a local index of source code, dependency and symbol relationships, Git history, tests, documentation, architectural decisions, dead code, and code-health signals, then exposes the indexed evidence through an MCP server, local dashboard, CLI, editor integrations, and pull-request analysis. Its graph is built from AST-parsed code and Git data, with confidence-stamped call resolution, change-impact and co-change analysis, hotspot and ownership history, documentation-drift checks, decision evidence, and deterministic code-health detectors. The MCP interface provides task-oriented tools for repository overviews, cited answers, file and symbol context, code search, risk analysis, change risk, architectural rationale, dead-code detection, and health and refactoring plans. Optional model-written documentation and prose can be generated through a configured provider, while the core graph, risk, health, test, and dead-code analysis does not require LLM calls or an API key. Repowise also includes reversible command-output distillation for agents, proactive context hooks, generated agent instruction files, a GitHub PR bot, multi-repository workspace analysis, contract and cross-repository blast-radius mapping, and a VS Code extension. It can be installed with pip and run locally; the repository states that raw source is processed transiently and not persisted, while indexed graph data, embeddings, wiki pages, and Git metadata are stored. The core project is licensed under AGPL-3.0, with commercial licensing available for specified enterprise capabilities and embedding scenarios.

codebase-memory-mcp is an MCP server from DeusData that indexes a codebase into a persistent local knowledge graph for AI coding agents. It parses source with tree-sitter AST grammars and uses Hybrid LSP semantic type resolution for selected languages to model functions, classes, call chains, HTTP routes, and cross-service links. Its MCP tools support code search, structural and Cypher-style queries, call tracing, architecture overviews, impact analysis, dead-code detection, and graph visualization. The project is distributed as native executables for macOS, Linux, and Windows, with no language runtime, hosted service, or API key required. Processing is local; the repository describes a RAM-first pipeline using compressed data, in-memory SQLite, and fused Aho-Corasick pattern matching, and reports sub-millisecond structural queries. A local visualization interface is available at localhost:9749.