
Uniprof
io.github.indragiekPublished by GitHub account indragiekv0.3.4Updated Oct 24, 2026
Universal CPU profiler designed for humans and AI agents
Overview
Uniprof is a local CPU profiler MCP server that lets an assistant profile applications across many language runtimes and analyze hotspots.
- What you can do
- Profile applications in Python, Node.js, Ruby, PHP, JVM, .NET, BEAM and native code without code changes or added dependencies, with the profiler chosen automatically from the command being run. Record profiles to a file for later use. Analyze recorded profile data to identify hotspots. Visualize results as a flamegraph in the browser. Check the environment and set up the MCP server for supported clients.
- When to use it
- Useful when you want an assistant to investigate why an application is slow, find CPU hotspots, or capture and compare profiles of scripts and services across different language runtimes.
- Requirements
- Runs as a local process via npm (npx uniprof mcp run) on macOS or Linux; Windows is not supported except through WSL2. Docker is recommended and used by default for containerized profiling; host mode needs the individual profilers installed. Native profiling needs debug information and frame pointers in the build.
Installation
In SourceWeft
- Open Uniprof in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
uniprof
uniprof simplifies CPU profiling for humans and AI agents. Profile any application without code changes or added dependencies.
Table of Contents
- Supported Platforms
- System Requirements
- Installation
- Quick Start
- Compiling with Debug Information
- Documentation
- Credits
- License
Supported Platforms
uniprof implements a common interface over multiple profilers that specialize in different platforms and runtimes. It automatically detects which profiler to use based on the command being executed, runs the profiler, transforms the varying output formats into a single format, and runs statistical analysis on the data to identify hotspots.
* Linux only for host mode
System Requirements
tl;dr: macOS or Linux with Docker installed
uniprof is designed to run on macOS and Linux but has primarily been developed & tested on macOS. If you find any bugs when running on Linux, please report them. Running on a Windows host is currenly not supported, but you can run on Linux installed on Windows via WSL2. Note that when using uniprof via WSL2, profiling native Windows executables is not supported, but you can still use the profilers for the higher level language runtimes like Python and Node.js.
Profiling tools are often non-trivial to set up correctly and can require elevated privileges. To simplify set up and provide better isolation for the profiled code, uniprof defaults to using Docker containers for each runtime that are pre-configured to run specific profiling tools. uniprof mounts your workspace in the container and executes the program with the profiler attached. uniprof also supports profiling outside the container if the host system has the profiling tools installed by running with the --mode host flag. The only case where containerized execution is not supported is when profiling a native Mach-O binary on macOS, since Apple Instruments cannot run inside a container.
Installation
MCP Server
Supported clients for auto-installation: amp, claudecode, codex, cursor, gemini, vscode, zed
If auto-installation is not supported for your client, add an MCP server using the stdio transport with the command npx -y uniprof mcp run.
For detailed MCP documentation see docs/mcp.md.
Quick Start
Profile and analyze in one step:
Save profiles to analyze and visualize later:
For detailed command line options documentation see docs/cli.md.
Host vs. Container Modes
Use the --mode option to control how profiling runs:
auto(default): Prefer container mode when Docker is available; otherwise use host.- Language runtimes (Python/Node.js/Ruby/PHP/BEAM/JVM/.NET) default to container for zero-setup.
- Native on macOS with Mach-O binaries uses host (Instruments). ELF binaries on macOS are supported in container mode.
- Native on Linux defaults to container; host can be used if you prefer your local perf setup.
host: Force host-installed profilers.container: Force Docker containers (not supported for macOS Instruments/Mach-O binaries).
Compiling with Debug Information
Native profiling requires debug information for meaningful results. Debug symbols enable the profiler to map memory addresses to function names, providing readable output instead of just hexadecimal addresses. Additionally, frame pointers improve call stack accuracy, especially for optimized code.
Documentation
Credits
- py-spy (MIT) is used for Python profiling. Included in the uniprof-python image.
- 0x (MIT) is used for Node.js profiling. Included in the uniprof-nodejs image.
- rbspy (MIT) is used for Ruby profiling. Included in the uniprof-ruby image.
- Excimer (Apache 2.0) is used for PHP profiling. Included in the uniprof-php image.
- async-profiler (Apache 2.0) is used for JVM profiling. Included in the uniprof-jvm image.
- dotnet-trace (MIT) is used for .NET profiling. Included in the uniprof-dotnet image.
- perf (GPL) is used for native profiling on Linux. Included in the uniprof-native and uniprof-beam images.
- speedscope (MIT) is bundled with uniprof and used for flamegraph visualization
License
All uniprof source code in this repository is licensed under the MIT License. See LICENSE.
uniprof downloads and runs Docker images that bundle third-party software. The Dockerfiles used to build these images can be found in containers/. These images and their contents are not covered by the MIT license and are governed by their own licenses. uniprof does not grant rights to those components and does not relicense them.
Source: README.md at commit e088547
Tools
0Version history
1- v0.3.4LatestSep 16, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts