"Executing Orders on Alpaca Trading Platform" matching MCP servers:

Analyzes codebases for cross-platform compatibility issues, detecting platform-specific APIs, file path problems, line ending inconsistencies, and shell command incompatibilities across Windows, macOS, and Linux.

Transforms codebases into a living knowledge graph with AI-powered code analysis, security scanning, and persistent semantic memory, leveraging Oracle 26ai vector and property graph capabilities.

MCP server that enables AI agents to analyze legacy code, plan and execute software migrations, generate modern source code, and validate production-ready artifacts through a multi-agent pipeline.

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.

Provides LLMs with code intelligence tools like relationship explanation, PR impact analysis, and health reports via the Model Context Protocol.

Enables AI agents to explain regex patterns in plain English and statically assess ReDoS risk before shipping, without executing the pattern or requiring an API key.

Exposes Beam's local, offline risk-scanning tools to any MCP-compatible host, enabling read-only heuristic detection of risky AI agent patterns without executing, blocking, or approving actions.

Code Intelligence Platform for AI Coding Assistants

Provides bounded, read-only analysis of local project directories, enabling inventory, marker detection, and safe file reads without executing code.

Enables static analysis of scripts without executing them, providing plain-English behavior explanations, decoded obfuscated content, IOC extraction, risk scoring, and MITRE ATT&CK mapping.

Automatically converts JoinQuant quantitative trading strategies to Ptrade platform format, supporting direct code input or file paths, with automatic API mapping and detailed conversion reports.

Analyzes codebases to suggest relevant learning projects and generate interactive slides with direct links to the Marble platform. It enables developers to create tailored learning experiences based on their specific technologies, patterns, and code context.

Offline PostgreSQL diagnostics: reviews SQL, risky migrations, candidate indexes and EXPLAIN JSON plans without database credentials or executing statements.

Enables deterministic verification for AI assistants by executing Python code that uses symbolic engines like SymPy and Z3 for math, logic, and code analysis.

Interact with CodeLogic, a Software Intelligence platform that graphs complex code and data architecture dependencies, to boost AI accuracy and insight.

Enables full ABAP development workflows against SAP systems via the ADT API, including reading and editing objects, running code, managing transports, executing tests, and performing code analysis.

An MCP server for auditing and analyzing user interfaces across 20 platforms based on 30 fundamental UX laws. It provides automated code detection, platform-specific checklists, and comparative analysis to optimize design usability.

Enables coding agents to query Python source repositories for exact and variant identifier occurrences with location and syntactic role, using deterministic AST-based evidence without executing code.

Enables planning safe file or export renames from a caller-supplied module graph, returning direct and indirect referencers, a mechanical edit order, and risk flags without reading, renaming, or executing anything.

Enables executing NXOpen C# statements in a running Siemens NX session and inspecting NXOpen DLL types, methods, and parameters through reflection.

Enables AI coding agents and MCP clients to query a live VSCode instance for real-time LSP diagnostics, hover/signature/type information, references, and workspace-wide symbol renaming, replacing slow tsc and eslint runs. Also supports opening files and executing VSCode commands through the bridge extension.

Enables MCP clients to run hardened, read-only radare2-based static binary triage tools, including disassembly, cross-reference following, string decoding, function renaming, and evidence-checked report generation without executing the sample.

A project intelligence platform for AI coding agents that scans, audits, generates, and monitors context files (CLAUDE.md, AGENTS.md, etc.) with drift detection and repair capabilities.

Enables MCP-compatible AI applications to perform read-only npm package and project dependency safety scans, returning proceed, caution, or block verdicts without executing package code.

Enables AI coding agents to query a running VSCode instance for real-time LSP data such as diagnostics, hover/definition/signature info, and symbol references instead of waiting on slow tsc or eslint runs. Also supports workspace-wide symbol renaming, opening files, listing workspaces, and executing VSCode commands.

Provides audit_plugin_health and prepare_semantic_review tools for deterministic inspection of Codex plugins and Agent Skills, generating evidence-backed reports without executing or transmitting target code.

Provides offline semantic validation for TcGen Structured Text (ST) review bundles by normalizing ST code, generating STruC++ tests from JSON specs, and executing them via the strucpp CLI.

Enables AI coding agents and MCP clients to pull real-time language-server diagnostics, hover/type information, reference navigation with usage context, and workspace-wide symbol renaming without running slow tsc or eslint checks. It also supports opening files and executing editor commands against a specific open workspace.

Enables listing available refactoring actions, executing validated JSON refactor plans inside Git transactions, and running a natural-language refactor loop with automatic verification and rollback via a local Ollama model.

Enables deterministic static analysis of Python code, providing tools to inspect classes, functions, imports, dependencies, and more, without executing the code.