"Generating a series of images using MCP from a sample image" matching MCP servers:

An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.

Enables AI agents to monitor Docker containers, system resources, ports, and logs in real-time.

MITM proxy MCP server that intercepts and verifies AI agent tool calls, detecting fabrication, tracking costs, verifying outcomes, and inferring user satisfaction.

Read-only MCP server for TrueNAS Scale debugging, providing k3s tools for kubectl operations and whitelisted midclt calls for system info, apps, and pools.

A secure MCP proxy server with JWT authentication, SQL guardrails, rate limiting, and Kafka audit logging, enabling enterprise-grade access control for MCP clients like Cursor and Claude Desktop.

Provides MCP tools to create and query SigNoz trace funnels, enabling agents to measure their own step conversion rates from within the agent loop.

Enables MCP clients to interact with a local AI agent through Ollama, providing tools for checking weather, current time, and available models, while tracing calls to Langfuse.

An MCP server for querying Grafana Loki directly with a discovery-first workflow — labels, values, series, and LogQL queries without requiring Grafana.

Exposes live industrial IoT telemetry to any MCP client, streaming simulated sensor data from a fleet of machines and detecting anomalies, with the ability to inject faults on demand.

Enables AI clients to run read-only network diagnostics over a sample multi-site topology, including site health, degraded sites, root-cause analysis, and redundancy gap detection.

An on-call agent for data incidents, built on a bio-inspired context protocol. It triages data quality and freshness issues using DataHub, computing severity, blast radius, and ownership from the catalogue before generating prose.

An MCP server that exposes GPU-accelerated anomaly detection to AI assistants via the Model Context Protocol. Provides two MCP tools: waveguard_scan (send training + test data in one call, returns per-sample anomaly scores and top explanatory features) and waveguard_health (check API and GPU status). Works on time series, JSON, numbers, text, and images — fully stateless.

Look up what the official MCP Registry declares for a server and what Lowdown observed: daily reachability, HTTP status, tool names and tool-schema changes over the last 30 days, plus outcomes reported by agents. A public time-series record for a fixed sample of 5,000 Registry servers. Recorded facts only, no scores or rankings. Raw data: CC BY 4.0.

A read-only MCP server for ClickHouse that enables AI agents to discover schema, sample data, and run read-only SQL queries to investigate observability data like logs, metrics, and traces.

Enables data observability operations with the Sifflet platform. Supports exploring assets, monitors, incidents, generating monitor-as-code YAML from descriptions, and performing impact analysis.

Enables local-first observability for MCP agent workflows by recording tool calls, prompts, latency, and token usage in a local SQLite database, and provides tools for inspecting, comparing, exporting, and generating dashboards from traces.

Lets coding agents read a local, redacted recording of the user's dev-browser session — pages, clicks, typed fields, API calls with their bodies, console errors and screenshots — so they can see what the user just did and what failed before asking. Exposes a recent-activity timeline tool with optional time, text and event-kind filters plus a tool that returns an individual screenshot as an image.

A TypeScript-based MCP server that enables users to interact with Prometheus metrics using PromQL queries and discovery tools. It allows LLMs to retrieve time-series data, metadata, alerts, and system status directly from a Prometheus instance.

Enables interacting with Prometheus through MCP for querying metrics, series, alerts, rules, and server status using natural language.

Enables LLMs to directly query a Matomo analytics instance, execute reporting methods, fetch historical trends, report metadata, and dynamically generated chart images through typed MCP tools.