Enables MCP-capable AI agents to control Windows desktops through UI Automation element trees, native screenshots, app launching, batched action sequences, smart waits, and safety gates using normalized coordinates.

Enables an LLM client to perform reverse engineering inside IDA Pro without the GUI, opening databases headlessly in persistent worker processes and exposing tools to decompile and disassemble functions, rename symbols, retype variables and arguments, add comments, and convert numeric bases. It can also run over stdio or HTTP transports and adopt an existing GUI session when desired.

Enables AI agents to query and trade through Interactive Brokers using 38 tools for order placement and management with risk checks, account and position data, market and historical data, and options analytics. Includes diagnostics and configurable safety limits, designed primarily for paper trading.

Causal memory layer for AI agents — MCP server that records decision→outcome relationships. Survives compaction.

Enables LLM clients to explore and query a local SQLite database through read-only, typed tools for table listing, schema inspection, ad-hoc SQL, customer lookup, and sales summaries.

Enables coding agents to run diff-scoped mutation testing on Python code, returning mutation scores and surviving mutants with actionable hints so they can improve tests.

Enables any MCP-compatible client to persist long-term memories for AI agents, with LLM-based fact extraction, semantic vector search, update/delete/list operations, and queue status checks across sessions.

Enables AI agents to operate a self-hosted double-entry personal finance ledger: answering spending, net-worth and cash-flow forecast questions, searching transactions, and managing schedules, rules and imports through audited, reversible tools. Read and write access is scoped by token, with privacy controls over what financial details reach the agent.

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.

Enables AI agents to test WCF/SOAP and REST services directly, with WSDL discovery, authenticated calls, and deterministic assertions. Supports YAML multi-step scenarios with variable extraction, JSONPath/JSON Schema checks, and CI runs without spawning PowerShell or curl.

Enables coding agents to check whether a GitHub issue is ready to hand off before starting work, predicting the files and tests the fix will touch from the live checkout and holding back under-specified issues with a single clarifying question.

A read-only MCP server that lets AI agents query a user's own Garmin Connect data via Garmin's official Personal API. It exposes activities, daily wellness metrics, sleep and recovery, and body/profile data as tools for natural-language analysis.

Enables agents to perform autonomous multi-angle specular glare healing and planar foil defect metrology by ranking candidate views, fusing glare-free views, and finalizing inspection or escalating unresolved cases through MCP tools.

Self-hosted daemon connecting Claude Code, Codex, and other coding agents across machines via MCP + A2A: delegate tasks, ask questions, share results, and wake sessions.

Enables unattended Claude agents to send Discord notifications and ask humans questions, receiving answers via buttons, selection menus, or thread replies, with pending answers recoverable on later runs.

Enables AI agents to prepare, launch, monitor, inspect, and recover existing Nextflow workflows through MCP tools, while client-side expert skills guide pipeline-specific input selection, parameters, QC, and troubleshooting.

Exposes agent-facing tools that let a personal AI agent submit each proposed action for an allow, require_approval, or deny verdict against OWASP PAA10 policy rules, plus tools to record provenance-tagged memories, log refusals, read status, and trigger a self-stop. Its decisions are advisory unless paired with the project's gating proxy or hook, which enforce them.

Enables MCP clients to manage Knowledge Agents and Jams, including creating and querying agents, uploading and inspecting documents, launching agent discussions, and retrieving responses and results.

Enables organizing personal contacts into concentric social layers, estimating warmth decay via an exponential half-life model, and scheduling mindful reconnection touchpoints within a weekly cognitive bandwidth.

Enables users to classify contacts into social closeness layers, estimate relationship warmth decay over time, and schedule intentional reconnections within a bounded weekly cadence.

This MCP server enables users to analyze personal reading and media streams by computing Shannon entropy, detecting Jaccard redundancy and echo chambers, and ranking content sources by decibel SNR to produce pruning recommendations and high-signal curation.

Enables users to audit personal reading streams by quantifying category diversity with Shannon entropy, detecting lexical redundancy and echo chambers via Jaccard similarity, and ranking content sources by decibel signal-to-noise ratio for pruning recommendations.

Enables agents to use ACT-R spreading activation memory, semantic association graphs, and automated memory consolidation via the Model Context Protocol.

Enables agents to guard external API calls with circuit-breaker health checks, success/failure reporting, and recovery state inspection, including exponential backoff with jitter and fail-fast rejection.