CodeCortex MCP server
by rushikeshmoreLets your AI understand your codebase's structure, risks and hidden file links before it edits anything.
AI Library · 4,066 MCP servers
Lets your AI understand your codebase's structure, risks and hidden file links before it edits anything.
Turn your project files into a searchable knowledge graph so your AI can answer questions about your past decisions and code.
Lets your AI map your codebase so it finds the right files and shows what a change would break.
Lets your AI search library documentation offline, using a local file instead of the internet.
Checks your API changes for breaking edits and leaked secrets, and keeps a signed record of what ran.
Lets your AI read and edit files, run commands, and take screenshots on your computer.
Check whether a claim is supported by the evidence, with a verdict and a confidence score.
Let your AI run commands in a lasting session on your computer, a server over SSH, or a Docker container.
Let your AI search a community knowledge base of real fixes for technical errors and problems.
Lets your AI explore your codebase as a map, so it can trace calls, data flow and structure without reading every file.
Lets your AI add login, a database, file storage and small server tasks to an app you are building.
Let your AI create realistic JSON test data from templates, straight from your chat.
Lets your AI look at running Java programs: memory, threads, logs, and class details.
Let your AI reach many MCP tools through one small, tidy connection instead of a huge list.
Check the MCP servers you use for broken tools, risky settings, and changes over time.
A command-line helper that lets you try out other MCP servers and see what they can do.
Lets your AI look inside a running Android or iOS app and even tap, change values, and take screenshots.
Lets your AI encode, hash, decode, format, and run network checks through onlinecybertools.com for you.
Let your AI write and check legal policies like privacy and terms pages from what your code actually does.
Lets your AI give each copy of a project its own set of ports, so parallel work never clashes.
Let your AI search a big directory of MCP servers, skills and plugins and hand you install commands.
Lets your AI map your codebase and jump straight to the files that matter instead of reading everything.
Your AI can record why code changed and look up those reasons later, so you stop guessing.
Lets your AI read code errors, jump to definitions, rename things and run language-specific helpers in your project.