"Fluent Bit" matching MCP servers:

Enables users to benchmark AI models across English, Urdu, and Roman Urdu by running question sets, grading answers, measuring confidently wrong and hedged responses, and producing reports, comparisons, and CSV exports through an MCP client or CLI.

Enables AI assistants and local workflows to run Jev-powered tools that judge speeches line by line, audit drafts against goals, bisect hard-to-test bugs, simulate common-sense physics, score note pairs, and ask arbitrary typed questions cheaply.

A comprehensive development toolkit with 23 tools covering code quality analysis, development efficiency, and project management. Enables AI-assisted code review, test generation, performance analysis, SQL generation, UI component creation, and automated project documentation.

Enables coding assistants to gather bounded source evidence, prepare typed judgments, and verify claims through MCP tools while leaving editing and execution to the host.

Provides AI agents with structured access to the OWASP Bug Logging Tool (BLT) ecosystem for logging bugs, triaging issues, and managing security workflows. It enables actions like submitting vulnerabilities, tracking contributor leaderboards, and awarding gamified bacon points through a unified interface.

Connects an LLM to specialized MCP servers via stdio, enabling authenticated GitHub repository, issue, file, and code operations alongside TF-IDF retrieval over employee PDF records and QA test-case generation and result validation. It exposes tools, a read-only resource, and reusable prompt templates so a client can discover and orchestrate multiple capabilities in one workflow.

Enables natural language interaction with the QIT CLI for testing WordPress/WooCommerce plugins. Supports running security, e2e, and activation tests, managing test environments, and accessing test results through conversational commands.

Enables AI-powered automated testing, security scanning, code review, and maintenance tasks directly within Claude Code or desktop.

Enables auditing coding-agent claims against local execution traces to detect contradictions, exposing session audits, recent failures, and optional scope-alignment triage.

Enables deterministic detection of pytest config-leakage that corrupts agent-benchmark grading, returning CLEAN/CORRUPTED verdicts and corrected pytest commands.

Enables AI clients to query and operate Git for a Cocos Creator 3.8 project and its submodules, drive editor asset/scene/prefab tools, and inspect the running preview's hierarchy, properties and page events through a scoped, token-gated bridge that previews every write as a one-time plan and never executes arbitrary code.

Enables AI agents and software engineers to investigate and resolve realistic distributed-system incidents using safe MCP-based diagnostic tools for code, logs, metrics, traces, database, and deployments.

Comprehensive MCP server for iOS Simulator automation, enabling AI agents to control simulators via tap, swipe, type, accessibility inspection, app debugging, and device management.

Enables agents to classify every claim into evidence tiers (FACT/INFERENCE/SPECULATION/UNVERIFIED) with attached evidence, forcing deterministic, evidence-gated reporting without LLM or network calls.

Enables AI coding providers to run structured multi-agent workflows with tracked tasks, handoffs, document specifications, and server-owned health gating and evidence. It coordinates roles like explorer, consultant, builder, and reviewer while keeping documents on the filesystem and task state in a database.

Enables coding agents to inspect live browser runtime evidence, such as blocking elements and interaction surfaces, and to independently verify whether a code fix resolved the issue.

Provides AI agents with a unified MCP interface for Android APK reverse engineering, metadata analysis, Smali/resource editing, rebuilding, signing, verification, and ADB device testing.

Lets any MCP-capable coding agent read and update an app's QA memory, test-case catalogs, coverage gaps, and Playwright run history. It exposes 11 tools covering status, scanning, case lookup, next-ID generation, memory search/add/forget, and result ingestion.

Enables MCP-based diagnostics and automation of Tauri 2 WebView2 instances on Windows, supporting discovery, snapshots, screenshots, and input control without Chrome DevTools or remote debugging.

Enables AI agents to test Telegram bots by driving the official Telegram Web client in a real browser, allowing visual verification of bot responses, inline keyboards, and Mini Apps.

Enables AI agents to directly inspect, configure, test, and orchestrate network devices through pyATS/Genie, including show command parsing, config rollback, feature state learning/diffing, fleet-wide command fan-out, and declarative test execution.

Enables AI coding agents to autonomously interact with, test, click inline buttons on, and verify Telegram bots end-to-end via MTProto.

Build three.js browser games on GrowBlocks with an AI assistant: read the API, play the game headless and see a screenshot after every change, reuse community blocks, and push an unlisted test build.

Enables spec-driven development acceptance gate with structured receipts, audit logs, and reviewer-ready evidence.

MCP server that enforces critical business invariants on AI-generated code changes, providing deterministic, evidence-backed ALLOW/BLOCK decisions before patches are accepted.

Gives your coding agent the review comments left on a running frontend with Maple. It lists open comments with the element, source location and screenshot they point to, waits for new ones, and resolves them when the fix is in.

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.

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