portgraph
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
portgraph
One line: npx portgraph (or bunx portgraph): live local port topology (Docker + Ollama/LM Studio/vLLM) as a terminal TUI and stdio MCP server.
Install
bunx portgraph
npx portgraph
# or install in your project / globally
bun add -d portgraph
npm i -D portgraphJSR:
bunx jsr add @kanchingyg/portgraph
npx jsr add @kanchingyg/portgraphcargo install --git https://github.com/kanchingyg/portgraphThe scan engine and MCP stdio server are written in Rust (src/lib.rs, src/main.rs, src/mcp.rs). TypeScript under src/*.ts is included for npx / bunx / JSR usage and MCP bridge helpers when no native binary is present.
Related MCP server: wharfy
CLI
npx portgraph
bunx portgraph
npx portgraph who :3000
npx portgraph kill :3000 --allow-write
npx portgraph --mcp
npx portgraph --mcp --allow-write
npx portgraph --mcp --dry-run # blocks mutating tools onlyMCP Tools Reference
Tool | Mutates | Description |
|
| List active TCP listening ports, owning PIDs, Docker container port mappings, and local LLM server tags (Ollama, LM Studio, vLLM). |
|
| Return the process ID, executable name, and command line bound to a specific TCP port. |
|
| Terminate the process listening on a port when |
Editor and Agent Integration
Cursor (.cursor/mcp.json)
{
"mcpServers": {
"portgraph": {
"command": "npx",
"args": ["-y", "portgraph", "--mcp"]
}
}
}Claude Code CLI
claude mcp add portgraph -- npx -y portgraph --mcpProgrammatic Usage (JSR / TypeScript)
import * as bridge from "jsr:@kanchingyg/portgraph/bridge";Runtime Safety and Guardrails
Stdio frame isolation: When
--mcpis active,hijackStdoutForMcp()redirects accidentalconsole.logcalls tostderrso JSON-RPC 2.0 frames onstdoutnever corrupt.Read-only by default: Mutating tools (
mutates: true) are blocked in--dry-runmode and require explicit--allow-writeauthorization.Loop breaker: Repeated identical
(toolName, args)invocations are hashed with SHA-256 and halted after 3 consecutive repeats to prevent runaway agent loops.Context budget truncation: Tool outputs are middle-truncated (
60%head /40%tail) scaled to the probed local modeln_ctx(Ollama/api/show, llama.cpp/props, vLLM/v1/models).Secret redaction and path normalization: AWS keys (
AKIA*,ASIA*), bearer tokens, andsk-*keys are scrubbed before returning tool output, and Windows drive paths (C:\...) translate cleanly to/mnt/c/...when WSL mode is enabled.
License
This server cannot be deployed
Maintenance
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Operate Linux, macOS and Windows from your LLM. Every action runs through an auditable allowlist.
Runtime permission, approval, and audit layer for AI agent tool execution.
Use a person's computer after they approve it there: files, Terminal, browser, local MCP.
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