"Personalized Summary Service" matching MCP servers:

A thin MCP server that wraps provenance-receipts and quality-gate services as tools, enabling AI agents to certify content origin and score quality via Ed25519-signed receipts.

Visual CVE audit dashboard for npm, Python, Go, and Rust projects. Scans your project manifests (package-lock.json, requirements.txt, go.sum, Cargo.lock) against OSV.dev live data, opens a browser dashboard for human review, then applies fixes only after explicit confirmation. Supports multi-service monorepos in one command.

MCP server that exposes the JsonFabrica API as tools, so an AI agent can generate realistic synthetic JSON test data while it codes — single documents or full relational batches from reusable templates, reproducible with a seed. Runs locally over stdio; no network service.

Test management over MCP: author test cases, run manual executions with per-case results, cut releases, and link automated tests to the cases they cover. Works against the hosted M00N Report service or a self-hosted instance.

Enables coding agents to see the UI they just changed without flooding their context window, returning a structured text summary (console errors, failed requests, overflow, layout shifts, accessibility violations) plus small crops of only the regions that changed since the last capture. All output is fitted into a chosen token budget, with captures stored on disk and evicted automatically.

Provides echo tools for testing MCP protocol functionality with message echoing, delayed responses, and JSON data analysis capabilities.

Connects AI tools to BlazeMeter's Service Virtualization platform, enabling natural language management of virtual services, transactions, and configurations.

Enables local auditing of trading strategies through MCP checkers for point-in-time data provenance, pre-trade order validation, and regime-fragility testing, while deferring promotion verdicts to a hosted service.

Detects schema mismatches between data producers and consumers through static analysis, supporting extraction, comparison, code generation, and automated validation with watch mode for MCP tools, APIs, and service contracts.

Provides browser automation tools for coding agents—goto, browse, goal, page_state, and summary—so agents can drive real pages through auditable, gated decisions and record traces for offline replay.

Enables UI debugging on physical iOS devices by bridging to an in-app DebugBridge HTTP service, supporting UI inspection, element interaction, log retrieval, and runtime validation.

Enables interaction with AWS Fault Injection Service to create, manage, and execute chaos engineering experiments. Operates in read-only mode by default for security, with optional write operations for starting/stopping experiments and managing templates.

Enables out-of-band interaction testing by integrating ProjectDiscovery's interactsh service as an MCP server. Allows AI agents to create callback domains, send probes, and capture DNS/HTTP interactions for security testing and verification workflows.

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.

Provides an Android UI automation service with an MCP server, enabling natural language control of Android devices, including clicking, typing, swiping, screenshots, and AI-driven understanding and debugging.

It enables AI agents and CI to run profile-driven SOAP/REST service tests with automatic login/session handling, test-customer locking, masked transaction-log/HAR catalog import, and cross-environment scenario execution.

Enables AI assistants to author, validate, inspect, and submit Neon3 NUI Flow interfaces through the Neon3 runtime, while managing app projects and diagnosing service state.

Local MCP service recommendations for BrowserAct, SearchApi, PDF.co, Make, Apify and Firecrawl. Install resultgate-pilot 0.3.1 with --referrals for six recommendation and evidence tools. Existing, local and free options take priority; BrowserAct affiliate links are disclosed. No provider execution, purchases or credential collection. Hosted /mcp is a separate authenticated simulation gateway.

Provides a reference MCP server that implements every MCP feature so client, gateway, and runtime authors can test against a single endpoint, and publishes a service contract describing its capabilities.

A Model Context Protocol (MCP) service that enables integration with Mantis Bug Tracker, allowing users to query and analyze bug tracking data through natural language commands.

Enables AI agents to connect to Charles Proxy for live and historical traffic analysis, summary-first insights, request detail inspection, and data-driven mock creation via Map Local/Remote.

Serves configurable fake service worlds as MCP tools with fault injection, recording every call and enabling seeded pytest assertions on final state.

Enables AI coding agents to request, check the status of, or withdraw a trial of a service virtualization platform, read agent-oriented documentation and trial onboarding guidance, and submit feature requests or feedback, all without an API key.

Enables interaction with Gremlin's reliability management APIs to monitor service dependencies, run reliability experiments, generate reliability reports, and manage chaos engineering tests through natural language queries.

Connects MCP clients such as Claude Code, Cursor and VS Code to a hosted QA service so the assistant can start and monitor test runs on a web app, explore its pages and flows, and read the bugs those runs uncover. Access is scoped by API key permissions, letting read-only keys list projects and issues while write-enabled keys trigger or stop runs.

Enables AI agents and assistants to dynamically add, update, and remove Mock Service Worker network mocks through MCP tools, with a WebSocket bridge that applies handler changes without restarting or reloading the application.

AI-native oscilloscope control. A pure-Python MCP service that lets LLM agents control Keysight EDUX1052G oscilloscopes via a compact DSL.

Enables AI incident-response agents to connect over MCP to a simulated service environment, receive alerts, gather diagnostic evidence, execute safe SOP actions, and verify recovery.

Enables AI agents and MCP clients to dynamically add, update, and remove Mock Service Worker network mocks via MCP tools, including live handler updates without restarting the application source code.

Enables users to manage, search, render, version, and regression-test local Markdown templates with typed variables, and to expose them as MCP tools and native prompts without requiring a model API, account, or cloud service.