An open‑source technical wiki connected to the systems it describes

CoexistAI is a modular, developer-friendly research assistant framework . It enables you to build, search, summarize, and automate research workflows using LLMs, web search, Reddit, YouTube, and mapping tools—all with simple MCP tool calls or API calls or Python functions.

MCP server for enabling LLM applications to perform deep research via the MCP protocol

Datadog MCP server for monitoring, metrics, logs, and dashboards

Enables AI assistants to perform read-only checks of sky positions against public astronomy archives, returning compact JSON verdicts and evidence for known transients, variables, TESS objects, asteroids, and other objects, plus observation planning and image links.

MCP observability: analyse MCP server usage, investigate sessions, and instrument MCP servers.

Query your AI agents' traces, errors, cost and alerts in Rius, the agent observability platform.

WoW: Forever lore and player-observed drops, vendors, quests, professions and talents, with sources.

Verified merchants accepting agentic payments on Lightning/L402/BOLT12/USDT — search, verify, pay.

Data observability tools for engineering teams: alerts, freshness, schema drift, lineage, quality.

Enables AI clients to inspect installed software packages and saved browser traffic through read-only local parsers, producing structured evidence about application structure, dependencies, endpoints, and observed authentication schemes.

Enables assistant clients to resolve artists and build or refine music, film, and book discoveries from selected taste seeds using Qloo, with follow/pass signals shaping subsequent recommendations.

Enables AI clients to observe foreground browser viewports, read filtered page evidence, and run guarded reusable site-pack procedures through the same local runtime as the CLI.

Enables AI agents and LLMs to persist facts, preferences, and observations in a local SQLite store and to build and traverse subject-predicate-object knowledge graphs across sessions. It provides fuzzy keyword search and graph queries so assistants retain context and recall prior project history without repeating prompts.

Exposes the full Plexim PLECS Standalone JSON-RPC interface as MCP tools, letting agents auto-start and connect to PLECS to load and edit models, run simulations and analyses, manipulate scopes and webserver data, and perform code generation or FMU export with structured, size-aware results. Includes write guardrails, concurrency handling for long simulations, and batch/raw passthrough escape hatches.

Enables AI clients to control and inspect a Unity Editor through MCP tools for scene and play-mode operations, logs, screenshots, assertions, Lua execution, UI interaction, world observation, and bridge management; advanced UI/Lua/world features require project-specific adapters.

Enables read-only access to Percona Monitoring and Management 2.x through PromQL metric queries and Query Analytics, so clients can list monitored databases, surface the slowest queries, inspect query details, and run validated SELECT queries against QAN's ClickHouse data. TLS verification, input validation, and Viewer-role tokens keep access strictly observational.

Exposes device discovery, capabilities, observation, logs, task execution and cancellation, and evidence retrieval as tools so MCP clients can run typed mobile automation tasks and inspect proof of completion.

Enables Codex sessions to observe and control the Windows desktop through screenshot reasoning, archived-frame inspection, pixel sampling, keyboard/mouse input, and workspace-local multimodal memory.

Enables agents to observe a desktop and perform mouse and keyboard actions through ESP32-based BLE or USB HID hardware, with local action translation and no second model in the MCP path.

The maia CLI and MCP server: start, drive, observe and stop swarms of Claude Code and Codex agents from a terminal, a script or another agent.

Manage employees, absences, clockings and schedules from an AI assistant.

Query your AI agents' traces, errors, cost and alerts in Rius, the agent observability platform.

Circulara Observe MCP plugin - meters your AI agents' token spend and carbon, free tier.