"Trade-In Value Estimator for Canada" matching MCP servers:

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.

Enables MCP-compatible AI clients to inspect Godot project and editor state, observe opted-in running scenes, manage processes, and apply permission-scoped guarded edits. It starts read-only and exposes additional capabilities only through explicit command-line flags.

Provides AI agents with ground-truth knowledge of Strapi projects by reading real schema files, enabling accurate queries and safe refactoring operations.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

Uses Claude as an independent second-model reviewer inside Codex, performing reviews on disposable Git snapshots with structured findings.

Enables Claude Code to leverage OpenAI models for expert code review, deep architecture analysis, and security audits, with automatic markdown report generation.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

MCP server giving Claude (and any MCP-compatible client) live access to SAP systems via ADT for reading, searching, editing, and activating ABAP objects.

MCP server that brings Trustabl static reliability scanning into Cursor, letting agents inventory agents/tools, flag risky patterns, score production readiness, and write SARIF reports.

Local memory for coding agents that can refuse, not only recall. A rule carrying a machine-checkable proof blocks the matching command before it runs, while prose-only rules can warn but never block.

An MCP server for interacting with the Rell Language Server Protocol interface. It enables LLMs to query LSP Hover and Completion providers for Rell projects.

An MCP server that empowers AI coding agents to work effectively with Minecraft mod development, providing static analysis of decompiled source code and runtime interaction with a running Minecraft instance.

A version-agnostic MCP server for Odoo that enables AI agents to interact with any Odoo app's data, schema, and source code, supporting tasks like data CRUD, schema mapping, code analysis, and feature implementation.

An intelligent, agentic MCP server gateway to OpenRouter's 200+ AI models. It provides budget controls, security features, semantic memory, and code search capabilities.

Enables LLM-powered agents to generate, execute, and analyze Alloy modeling language code for software modeling and formal verification. Provides tools to run Alloy models, access documentation and examples, and generate models from system descriptions.

Provides ChatGPT read-only access to inspect repositories, code, merge requests, pipelines, and CI logs on self-managed GitLab instances, including those reachable only from a private network or VPN.

Enterprise-grade MCP server for SAP ABAP development, enabling AI-powered coding assistance through Amazon Q Developer and Kiro with 15 SAP development tools.

Enables Claude Code to use VS Code's tools, including diagnostics, symbol renaming, command execution, file opening, workspace listing, semantic search/API reference, terminal context, and integrated browser page interaction. It lets Claude see and act on the user's VS Code window, including shared browser pages and Markdown Editor selections.

MCP server for ai-scanner that enables AI agents to scan codebases for LLM usage, AI frameworks, and exposed secrets.

Enables a sandboxed Claude Code session to see editor selections, review proposed edits as VS Code diffs, and read workspace diagnostics through an MCP-over-WebSocket IDE bridge.

Provides token-efficient code retrieval for coding agents by indexing repositories and enabling ranked snippet search, symbol outlines, and surgical line reads.

An MCP server that provides a semantic index and 14 bounded tools for AI agents to navigate Excel workbooks by symbols, references, and diagnostics, avoiding the need to read entire rows.

Enables AI assistants to interact with VS Code for language intelligence, debugging, and code execution.

Enables agents to inspect native binaries, JavaScript and Electron apps, .NET assemblies, and websites, returning code, references, and evidence-backed findings for understanding and reimplementing features.

Enables Codex to access C# diagnostics, navigation, and refactorings through the official Roslyn language server, including definitions, implementations, references, renames, fixes, and refactorings.

Enables AI assistants to import binaries into Ghidra, trigger analysis, browse functions, symbols, strings, and imports, and read decompiled C code and disassembly via MCP tools.

Enables AI assistants to analyze project folders for dependencies and frameworks and fetch current documentation or datasheets from the web.

Enables LLMs to analyze Python repositories structurally via AST and call graphs, providing code search, symbol lookup, change-impact analysis, workflow tracing, and explanation without embeddings.

A Model Context Protocol server that extracts embedded data (such as i18n translations or key/value configurations) from TypeScript/JavaScript source code into structured JSON configuration files.

Record Python/Rust/TypeScript program runs to local SQLite; query call trees, exceptions, and value flow over MCP — refuses rather than guesses. Not the unrelated Telegram sensorium-mcp.

Gives coding agents offline, local lookup of real MetaTrader 5 built-in function signatures, sections and documentation links, plus plain-language meanings for trade server return codes and runtime errors. It runs over stdio with a prebuilt index, making no network calls and requiring no API key, so agents stop emitting MQL4 syntax or inventing functions.

MCP server that connects AI coding agents to Pernosco debugging sessions for querying execution traces, inspecting variables, navigating call stacks, and tracing value histories through natural language.

Finds the closest Tailwind CSS palette colors to any given CSS color value. Supports multiple color spaces and customizable result filtering to help match designs to Tailwind's color system.

Enables exhaustive, unit-by-unit analysis of open-source repositories through MCP, cataloging every file and symbol, resolving dynamically built routes and URL paths, and mapping call and value flows via LSP and Joern. Every conclusion carries file:line evidence tied to a pinned commit, with unresolved items tracked in an unverified list and assigned verification grades L0–L2.

Enables an AI assistant to inspect GDSII layouts and stackup files, validate model scripts without running them, and generate AWS Palace models locally, along with layout previews, gmsh visualisation, S-parameter summaries, and inductor/capacitor value extraction. It works on files in the user's own Python environment and disk, without invoking the Palace solver.

Enables MCP-compatible AI coding agents to obtain clean failing-test context, ranked suspect lines, runtime value comparisons, bounded code search, and patch verification so they can fix Python test failures with fewer tokens.

A verification infrastructure and MCP server that specializes in refutation (negation) rather than generation, providing tools for counterexample search, Lean verification, and audit chains with a 4-value verdict system.

Enables asking a consuming app in plain language to audit its design system usage, returning tables that sort every value and component by origin—design system, app-named, or none—along with token and contrast checks.

Enables deep, order-independent comparison of JSON files to detect differences including missing keys, value mismatches, and type differences. Provides detailed reports with path tracking for precise identification of variations between JSON structures.