lspeek.win-x64 1.0.46

lspeek

A toolkit for interactively driving Language Server Protocol servers — send requests, inspect responses, watch logs and work-done progress, and reproduce LSP bugs against a local build.

A single backend owns the LSP server (spawns it, forwards requests/notifications, auto-answers infrastructure requests, and records every frame in both directions). Three thin frontends drive that backend over a local HTTP + Server-Sent-Events API on 127.0.0.1:

• TUI (lspeek) — a Spectre.Console terminal UI.
• MCP server (lspeek-mcp) — exposes the backend as agent-callable MCP tools.
• Canvas extension (lspeek-canvas) — a GitHub Copilot CLI canvas with a clickable timeline.

Every frontend spawns its own private backend (one live server per TUI/MCP process and per canvas instanceId); they don't share a session. The three frontends expose the same action surface, so the server is driven the same way regardless of which you use.

Architecture

flowchart LR
    TUI["lspeek (TUI)"] -->|HTTP + SSE| BE
    MCP["lspeek-mcp (MCP)"] -->|HTTP + SSE| BE
    CANVAS["lspeek-canvas (canvas)"] -->|HTTP + SSE| BE
    BE["lspeek-http<br/>(HTTP+SSE host)"] -->|stdio JSON-RPC| LSP["language server<br/>(e.g. Roslyn)"]

The action surface

All three frontends expose the same actions (the MCP tool names are these action names; the canvas calls them via invoke_canvas_action; the TUI maps its UI / JSON scripts onto them):

See skills/lspeek-control/SKILL.md for the full message-composition guide (initialize handshake, loading the workspace, reading diagnostics/progress, gotchas), and skills/roslyn-lspeek/SKILL.md for Roslyn-specific local-build details.

Installing

Both .NET frontends ship as .NET tools that are self-contained and platform-specific, with a self-contained copy of the backend bundled inside the package (under tools/any/<rid>/backend/). An installed tool carries its own runtime and spawns its bundled backend — no .NET runtime and no extra setup required:

dotnet tool install --global lspeek        # the TUI
dotnet tool install --global lspeek-mcp    # the MCP server

dotnet tool install reads each tool's RID manifest and fetches the payload matching your machine. The frontends are published for the full RID set — win-x64, win-arm64, linux-x64, linux-arm64, linux-musl-x64, linux-musl-arm64, osx-x64, osx-arm64. To run without installing, use dnx lspeek … (the TUI) or point your agent at the packed lspeek-mcp.

Building

dotnet build lspeek.slnx

This builds the backend (lspeek-http) alongside the frontends. The TUI, MCP, and canvas discover and spawn the backend automatically. The .NET frontends (TUI, MCP) look, in order, for:

1. the LSPEEK_HTTP environment variable, if set (a host file, or a directory containing it), then
2. a bundled backend/ subdirectory beside the frontend (AppContext.BaseDirectory/backend/).

Packaged tools ship a self-contained copy of the backend in that backend/ folder — a platform-specific apphost run directly; a local dotnet build copies the backend's managed build output there instead (run via dotnet exec). Either way the same backend/ probe finds it.

The canvas extension can't bundle a .NET app, so it uses the in-repo dev build, then falls back to dotnet dnx lspeek-http — fetching the published backend tool from NuGet (a self-contained, ReadyToRun, platform-specific build for every supported RID; cached after first run) so it works off-repo with only the .NET SDK installed. See the canvas section for details.

Set LSPEEK_HTTP to override discovery for the .NET frontends (TUI, MCP) — e.g. point them at one freshly built backend while iterating on it.

TUI (lspeek)

lspeek <server> [--no-init] [--json <PATH>] [--exit]      # installed global tool
dnx lspeek <server> [...]                                 # or run without installing

Examples

lspeek roslyn                          # launch and connect to Roslyn
lspeek roslyn --no-init                # skip handshake
lspeek roslyn --json replay.json       # run a script then enter TUI
lspeek roslyn --json replay.json --exit # run a script and exit
lspeek ./my-server.json                # use a custom server config

Use X in the TUI to export a session as a replayable script.

MCP server (lspeek-mcp)

A stdio MCP server that exposes the action surface as tools, each driving this process's own private backend. Register it with your agent's MCP configuration, pointing at the installed lspeek-mcp command (after dotnet tool install --global lspeek-mcp) or at dotnet run --project src/Client.Mcp. stdout is reserved for the MCP protocol; logs go to stderr.

Each tool returns a JSON envelope: { ok:true, ... } on success or { ok:false, error } on failure.

Canvas extension (lspeek-canvas)

A GitHub Copilot CLI canvas that spawns the backend, proxies every action over HTTP, and shows the backend's web UI (a clickable timeline of all traffic with a manual JSON send box). It lives in this repo under .github/extensions/lspeek-canvas, so the Copilot CLI auto-discovers it when working in the repo. Confirm it loaded with list_canvas_capabilities(canvasId:"lspeek-canvas"), then open_canvas and drive it with invoke_canvas_action({ instanceId, actionName, input }).

Running off-repo (no local build)

The canvas is two small JS files — it can't bundle the .NET backend the way the packaged tools do. Instead, when it can't find an in-repo build it runs dotnet dnx lspeek-http, which downloads the published backend tool from NuGet on first use, caches it, and launches it. So the only prerequisite off-repo is the .NET SDK (which provides dnx).

The backend ships as its own lspeek-http tool, published as a self-contained, ReadyToRun (R2R), platform-specific build for every supported RID (win/linux/osx, x64/arm64, glibc/musl) — a self-contained executable that bundles the .NET runtime, so the backend needs no .NET runtime of its own. R2R cross-compiles, so all RID payloads are built on a single runner. dnx reads the package's RID manifest and fetches whichever payload matches the current machine.

Built-in Servers

Custom Server Configuration

Point <server> (TUI) or the server option (MCP/canvas) at a JSON file to connect to any LSP server:

{
  "name": "my-server",
  "command": "path/to/server",
  "arguments": ["--stdio"]
}

Scripting (TUI)

Sessions can be automated with JSON script files. A script is a JSON array of messages to send:

[
  {
    "type": "request",
    "method": "textDocument/hover",
    "params": {
      "textDocument": { "uri": "file:///path/to/file.cs" },
      "position": { "line": 10, "character": 5 }
    }
  },
  {
    "type": "notification",
    "method": "textDocument/didOpen",
    "params": { "textDocument": { "uri": "file:///path/to/file.cs" } }
  }
]

In script mode, status/progress is written to stderr and per-message results are written to stdout. When you use --json, lspeek does not send initialize or initialized automatically; if the session needs that handshake, the script must include it explicitly.

Each entry supports:

Repository layout

src/
  Client.Core/        LSP session library (raw transport, message buffer, server resolution)
  Client.Protocol/    shared DTOs + C# BackendClient
  Client.Backend/     lspeek-http: HTTP+SSE host (owns the server, serves the UI)
  Client.Tui/         lspeek: terminal UI
  Client.Mcp/         lspeek-mcp: MCP stdio server
.github/extensions/
  lspeek-canvas/      canvas extension (thin client over the backend)
skills/
  lspeek-control/     how-to skill for driving any LSP server (generic)
  roslyn-lspeek/      Roslyn-specific how-to (local builds, project loading)
tests/
  Tests.Integration/  raw-client, message-buffer, and surface-parity tests