Enables an LLM agent to investigate a Kong Gateway through fourteen read-only, schema-validated tools and a deterministic diagnostic engine, so it can trace routes, services, plugins and upstream health and explain faults such as why authentication is failing on a path. Every fact comes from the gateway itself, and the model only selects tools and writes the evidence-backed explanation.
Enterprise AI operator evaluation MCP server. 27 tools
(22 read + 5 write) for measuring, benchmarking, diagnosing, and interv
ening on how human operators use AI tools across 5 canonical metrics.
Governed, read-only OT data tap for substation and utility telecontrol — IEC 60870-5-104, DNP3/IEEE 1815, and IEC 61850 MMS connectors with cross-protocol asset discovery, alarm and downtime RCA, unbypassable audit logging (MCP + CLI), budget/runaway guards, and an airgap no-egress mode. Energy edition of Industrial-AIOps, built on iaiops.core.
Ask your AI agent about your MCP servers: which tools fail, how a release compares, what clients look for and do not find. Reads from mcpspan with a read token.
Enables AI agents to debug and repair historical Solaris/SPARC systems by providing an out-of-band control plane with guest DTrace, QEMU monitor access, SPARC-aware GDB, host eBPF/perf tracing, and an immutable evidence ledger for cross-layer hypothesis testing.
Enables coding agents to read a replay link or a gn-tracing-*.zip package, surfacing console errors with source-mapped stacks, failed requests, and the user timeline.
Connects AI-powered tools to the Confident AI platform for evaluating, observing, and iterating on AI quality, enabling cloud evaluations, dataset management, prompt versioning, production tracing, and human annotations directly from editors like Cursor and Claude Code.
Ships only the MCP server, not the recorder.
Recording works by wrapping a process on the host — a local proxy, a PATH shim, a shadow git
index. None of that survives a container boundary, so orca record inside here would watch an
empty namespace. What does travel is the read side: the six MCP tools serve runs that already
exist on disk, so a client mounts its .orca directory and r
Enables users to log AI tool activity without conversation text and contribute back only user-approved, small-cell-suppressed counts through a local MCP interface.
Enables grading a website's security headers with per-gap fixes and a README badge, and analyzing logs, code, configs or suspicious messages to determine what happened, how severe it is, and what to fix first. Requests are masked for sensitive data and automatically retried across multiple AI providers when one refuses, subject to a defensive-use-only policy.
Provides structured MCP tools for local runtime observability and debugging of React Native/Expo apps on Android, enabling evidence-first diagnostics such as screenshots, UI trees, per-request network capture, performance metrics, and CDP-based console/heap/profiling exports.
Enables AI agents to analyze, cluster, compare, and export reports from local log files through seven read-only tools, returning compact evidence packs with line-number citations instead of raw log dumps. All processing happens on the local machine, so log data never leaves the environment.
Provides read-only, multi-vendor network device interaction, configuration auditing against vendor-guide rules, and safe diffing of proposed changes for AI agents to inspect and analyze network infrastructure without any commit or write capability.
MCP server that diagnoses ML model regressions by correlating drift reports, eval runs, and deploy logs, providing evidence-cited incident reports through a set of investigation tools.
Enables any MCP client to watch a running DSH agent and steer it mid-flight, streaming thinking, tool and file notifications while sharing intent and exposing a floor lock that denies the agent's writes while held. It also lets clients interrupt the current turn with an injected alert and delegate reviews through an on-disk inbox.
An MCP server that enables conversational interaction with Wazuh SIEM, allowing users to investigate alerts, hunt threats, tune false positives, edit rules, and run security actions via natural language.
Enables read-only querying and analysis of Kibana logs through a logged-in sid Cookie, including keyword/time/index searches, traceId lookups, surrounding log context, and aggregations by service, level, or host. It also validates Kibana connection status and redacts sensitive fields such as cookies, tokens, and passwords.
Enables AI agents to query and analyze Graylog logs through MCP tools for search, aggregation, stream listing, and saved queries, with optional OpenAI-powered natural language orchestration and audit logging.
Enables MCP-compatible clients to inspect the local machine's CPU, memory, and disk information through tools, a structured resource, and an upgrade-assessment prompt.
Enables querying and managing AI logs through tools like listing logs, retrieving jobs, and performing AI-powered chat queries. Also provides access to gateway security reports and guardrail testing.
An MCP server for querying Grafana Loki directly with a discovery-first workflow — labels, values, series, and LogQL queries without requiring Grafana.
An MCP server that records agent execution metrics and exposes a Context Window Explorer to visualize exactly what entered the model's context window across sessions, tokens, and tool calls.
Provides cryptographically signed, tamper-evident compute usage receipts via a Model Context Protocol server, exposing tools to record usage, verify receipts, list the ledger, and verify ledger integrity without requiring any account, API key, or single cloud provider.
Web analytics and AI session replay for agents: visitors, breakdowns, funnels, goals, revenue attribution, and AI-found site issues. Connects to the hosted Flowsery MCP server.