"PulseFeed - Content or News Feed Platform" matching MCP servers:

Demonstrates agent-native platform onboarding with human-in-the-loop API key provisioning, plus live usage and rate-limit queries via Anthropic Admin APIs.

A read-only MCP server that enables AI agents to act as GCP platform engineers, allowing them to investigate incidents, take inventory, and find cost-optimization opportunities in Google Cloud projects without mutating any infrastructure.

Read-only MCP server that exposes Kubernetes platform state (tenants, pods, SLOs, ArgoCD applications, chaos schedules, and catalog services) to AI agents, enabling natural language queries about cluster health and configuration.

Lets your coding agent talk to the RunWhen platform — workspace chat, issues, SLXs, run sessions, and the Tool Builder — over the Model Context Protocol. Enables workspace chat with AI assistant, task authoring via Tool Builder, and direct data access to workspaces, issues, SLXs, run sessions, and more.

Enables DevOps operators to query and operate the Sigma Streaming Platform from any AI client such as Claude Desktop, Cursor, or Kiro.

Enables approval-gated incident response workflows that gather evidence through read-only MCP tools, perform idempotent writes, and preserve a durable audit trail.

Provides AI agents with real-time access to live Azure infrastructure, including AKS cluster health, resource management, policy validation, and Terraform analysis through a Model Context Protocol interface.

Enables ingestion and full-text search of Windows application logs via MCP tools. Supports dual-backend indexing with Elasticsearch and SQLite for fast retrieval.

Enables read-only diagnostics of Google and Microsoft Merchant Center shopping feeds, including feed health, product disapprovals, cross-platform comparisons, prioritized fix plans, and optional live landing-page JSON-LD/meta checks.

A FastAPI-based server that enables executing SQL queries, managing database connections, and retrieving analytics reports through MCP-integrated endpoints. It allows users to interact with database schemas, performance metrics, and access logs using structured queries.

Enables AI assistants to interact with SMB platform APIs for querying business data, managing tasks, accessing connectors, dashboards, and monitoring security.

Enables reading and building Splunk dashboards via the management REST API, using SSO for permissions and supporting both Studio and Classic formats.

Enables users to inspect ephemeral GitHub Actions runner fleet status, SLOs, incidents, capacity recommendations, and cost evidence through read-only MCP tools, without allowing infrastructure or cluster mutations.

A standalone Python/FastAPI server that implements the Model Context Protocol (MCP) for the OPTIX threat intelligence platform. It exposes 26 analyst-friendly tools that AI assistants and programmatic consumers can use to query threat feeds, search documents and indicators, manage watchlists, triage IOCs, generate detection rules, trigger AI research, and produce intelligence reports.

Enables comprehensive NIST Cybersecurity Framework 2.0 assessments with 40+ MCP tools for maturity scoring, gap analysis, implementation planning, risk assessment, and executive reporting across 740 security questions.

Enables named, authenticated callers to run read-only introspection of a Google Cloud project and to read and write per-tenant notes that stay isolated between callers. Every request is scope-checked against a reviewed policy, rate-limited per caller, and audited without ever logging argument values.

A high-performance MCP server integrated with a Django analytics dashboard, featuring 19 tools for AI interaction tracking, AST code analysis, and real-time token efficiency metrics.

Competitive intelligence platform with 24 tools. Monitor competitor pricing, content, positioning, tech stacks, and AI visibility — track how ChatGPT, Claude, and Gemini rank your brand.

Enables querying the current state, incident history, resolution times, and feed URLs for over 1,100 SaaS/cloud vendor status pages.

MCP server for Chainlink ecosystem monitoring with 6 tools: price feed tracking, VRF monitoring, automation status, CCIP tracking, and staking analytics. MIT licensed.

Enables AI agents to search and inspect a real-estate catalog, record client inquiries, and check data-feed health, with per-identity tool permissions, hashed bearer tokens, rate limiting, and PII-free audit logging. The feed is validated item-by-item so broken records are dropped and reported before they reach the model.

Enables AI-assisted management of multi-vendor network devices (Cisco, Juniper, Nokia, Arista, Linux) through natural language, supporting health checks, configuration changes, routing analysis, and automation workflows.

A lightweight MCP server that enables AI assistants to execute local development tools and retrieve system status with low latency over stdio or HTTP.

Enables classification of GPU workloads as training, inference, or idle from telemetry data, with tools for one-shot classification, benchmarking, and audit log verification.

16-tool MCP server for Google PageSpeed Insights & Chrome UX Report APIs. Analyze, compare, and optimize web performance directly through Claude, Cursor, or any MCP-compatible AI client.

Read-only MCP server for Grafana Loki: lets AI agents (Claude Code, Cursor, Copilot) discover labels, read bounded LogQL pages, count lines by label or time, and export logs — across several Loki stands

MCP server exposing rlg (RustLogs) log files as tools for on-call / SRE agent workflows. Three tools over JSON-RPC stdio — tail_log (last N events, filtered by level/target), filter_log (predicate filtering), summarize_errors (grouped error taxonomy). Pure Rust. MIT OR Apache-2.0.

A read-only MCP server that reports BI pipeline readiness, blockers, and the next allowed action for governed Power BI workflows. It never writes files, executes warehouse work, or grants human approvals.

Enables agents to fetch app reviews from Apple's App Store and Google Play per country store, newest first, filtered by date or star rating, with each scheduled run returning only reviews not seen before. It also returns a per-app, per-country rating trend row with the current rating, rating count, change since the last run, and the star split of new reviews.

Enables AI agents to self-report bugs, ambiguities, and improvement requests via a single report_issue tool, logging to PostgreSQL or JSONL with severity and mode classification.