"Information on LinkedIn Business or LinkedIn Advertising" matching MCP servers:

Enables developers and product owners to scan a codebase and extract a readable business overview—features, roles, access control, data model, and endpoints—along with findings on missing or inconsistent rules, and generate shareable HTML or Markdown reports and diagrams.

Exposes structured Microsoft Dynamics 365 Business Central source code (versions 23-29, 47 localizations) to AI agents via MCP, enabling fast lookups, searches, and code analysis.

Allows Claude Code to request an independent code review from Google Antigravity (Gemini, Claude, or GPT-OSS) via the Antigravity CLI, providing a second opinion on plans or diffs.

Enables an AI assistant to debug ABAP code on a connected SAP system by setting breakpoints, running code, and capturing call stacks and variables, with one-shot or interactive stepping.

Gives an AI agent complete knowledge of a specific DevExpress XAF application: its entities, controllers, actions, business rules, Model Editor customizations, custom property editors and the version-gated data migrations that ran once on a production database. Reads the source with Roslyn without compiling it, so it works on a branch that does not build and needs no DevExpress licence.

Provides access to Ant Design component library documentation and information for automated code generation. Enables searching components by category or keyword, retrieving component props, examples, API documentation, and available icons.

MCP server that provides npm package information for AI agents during TypeScript development.

Enables consulting oracle AI models (Codex or Claude) for expert reasoning and analysis on complex problems, architectural decisions, and design tradeoffs through a unified CLI interface.

An MCP server that scans codebases to extract structural information (classes, functions, etc.) with flexible filtering options and outputs in LLM-friendly formats.

Enables local detection of protected health information in source code before it reaches LLM prompts, log statements, or analytics calls.

Lets AI coding agents read an outline of a large file or a digest of noisy command output instead of the full text, while every hidden line stays retrievable on disk through a run handle. Agents can request only the line ranges, slices, or grep matches they need and list recent runs, cutting token spend without losing information.

Enables AI assistants to search code summaries using Chinese business terms, with support for semantic search and PRD linkage.

Provides AI tools with access to real-time web search, automated code reviews, and detailed Korean business information through the AgentSkills API. It enables users to perform structured searches, analyze code for security and performance, and retrieve Korean company financial data.

Enables Claude to scan a website or its code to find suitable directories, guest-post and resource-page prospects, score them, locate contact emails, and draft outreach emails and consistent business listings for any niche and country. It also tracks each prospect from todo to live and verifies that placed links exist, are follow or nofollow, and remain live.

Enables running Prospector static analysis on Python files or directories via MCP, returning structured results with severity, location, and rule codes.

Enables cleaning and sanitizing prompts through an LLM-powered tool that removes sensitive information, provides structured feedback with notes and risks, and normalizes prompt formatting. Supports configurable local or remote OpenAI-compatible APIs with automatic secret redaction.

Enables coding agents to navigate and query source code by providing context, symbols, and call graph information through a graph index.

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.

Enables a coding agent to inspect Go HTTP endpoints and their MySQL table interactions, view SQL/source evidence, and collaboratively create or update diagram tabs on a shared browser canvas via MCP.

Enables agents to query TypeScript and JavaScript code intelligence—type diagnostics after edits, go-to-definition, references, hover information, and document symbols—through MCP tools.

Local MCP server to index your codebase once and search it across AI sessions with keyword, semantic, or hybrid search, keeping all data on disk.

An MCP server that enables AI assistants to parse Xcode and Swift build outputs into structured, token-efficient formats like JSON or TOON. It provides tools for executing build commands and extracting detailed diagnostic information such as errors, warnings, and test failures.

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 AI coding agents to inspect Runable projects over MCP, providing read-only access to project information and configuration via Runable's inspector.

https://gopls-mcp.org/ MCP server for golang projects development: Expand AI Code Agent ability boundary to have a semantic understanding and determinisic information for golang projects.

Enables AI coding agents and MCP clients to retrieve real-time editor diagnostics, LSP type and symbol information, code references, and perform workspace-wide symbol renames without waiting for slow separate build or lint commands.

Enables AI assistants to check code changes against architecture and business rules, assess dependency impact before edits, verify violations after edits, and record tamper-evident audit evidence through MCP tools.

A contract linter for AI agents that uses structured YAML contracts to define dependencies, business rules, and exports, enabling agents to work without breaking project conventions.

Enables MCP-compatible AI coding agents to access real-time VSCode diagnostics, LSP type/symbol information, references, code navigation, and safe workspace-wide symbol renaming without waiting for slow tsc or eslint checks.

Enables MCP-compatible AI coding agents to retrieve real-time language-server diagnostics, type and symbol information, definitions, references, workspace-wide renames, and file operations from an open editor. This provides accurate code navigation and editing context without waiting for slow tsc or eslint checks.