"Local AI Agent Toolkit" matching MCP servers:

Enables AI agents to manage prompts and sessions via the ai-agent-logs API, with tools for health checks, login, listing/creating prompts, and retrieving sessions.

Exposes read-only tools for OPC UA PLC tag monitoring and diagnostics, and enables template-driven, validated IEC 61131-3 SCL code generation with a mandatory human review gate before download.

MCP server providing read-only operational tools (logs, metrics, traces, service health, config) for troubleshooting an environment, with one exception for toggling chaos scenarios.

Enables AI agents to analyze text and retrieve real-time system metrics such as CPU, memory, and uptime through LangChain tool calling, with an embedded web UI for testing queries and viewing tool execution logs.

Enables natural language queries for device support, including resolving device references, retrieving device details, historical metrics, and checking provisioning status. Maintains conversation context for multi-turn interactions.

Enables AI SRE agents to query a DynamoDB incidents table using short-lived, read-only STS credentials, with no standing AWS access keys.

Provides a Twitter-like timeline interface where AI agents can post thoughts and progress updates in real-time while working on tasks. It enables users to monitor agent activities through a web GUI and persistent database storage for debugging and session tracking.

A Model Context Protocol server that provides LLM Agents with a comprehensive toolset for IP geolocation, network diagnostics, system monitoring, cryptographic operations, and QR code generation.

MCP server that diagnoses Apache Spark job failures and optimizes performance using stack-trace analysis and LLM providers, supporting EMR and local sources.

Enables querying Margint per-customer AI margins and costs from MCP clients. Provides tools to list customers, drill into costs, check budgets, and view workspace-wide cost breakdowns.

Registers a set of inert, tempting decoy tools with any MCP-capable client so that any call from a hijacked or prompt-injected agent instantly raises an alert with full attack context and a per-call trace token. Also plants worthless canary tokens in honeypot files that trigger zero-false-positive leak alerts when they surface in agent output, files, or outbound requests.

Exposes network-monitoring tools (query metrics, analyze windows, compare, logs, status, runbooks, speed tests) as an MCP server for agentic workflows. Designed with evaluation suites, cost-aware model routing, and semantic tool retrieval.

Provides cost analysis of AI agent usage by previewing scrubbed metadata before upload and analyzing spend, cache-hit rates, and waste recovery through a local or remote server.

MCP server for AI agent observability, providing trace and span logging, search, latency/tokens/cost metrics, and anomaly detection using an in-memory buffer.

A read-only MCP server that exposes AI Disk Doctor Core's scan, model inventory, and history tools via local stdio, with no mutation or shell capabilities.

Tracks AI agent token usage and spending in real time, with budget alerts, per-task cost breakdown, and a visual dashboard.

A read-only MCP server for querying AI provider administration APIs, providing normalized usage, cost, and dashboard data for OpenAI and Anthropic.

AI development observability platform. It silently captures structured data from vibe coding sessions via MCP and codifies deviation patterns into project rules to make AI write better code. 100% local and zero runtime dependencies.

Enables querying PostHog with HogQL, retrieving event and property definitions, session replays, and project lists, plus optional REST API access with safeguards against accidental writes and API key leakage.

A simple MCP server providing ping, echo, and TCP host health-check tools with latency measurement. It enables transport testing and real network connectivity checks through natural language.