mcp-language-server
mcp-language-server gives MCP enabled clients access semantic tools like get definition, references, rename, and diagnostics.
Runssource: GitHubGoBSD-3-Clausecommit e4395849a52e
Go, BSD-3-Clause licensed. The project labels itself: ai, language server protocol, mcp, mcp server and model context protocol.
mcp-language-server runs. An Argusic agent installed it in 67 minutes and hit 9 errors on a clean machine with no GPU, and the whole session was recorded.
The MCP language server builds and runs; it initializes as an MCP server, connects to gopls, pyright, typescript-language-server, and rust-analyzer via stdio, and exposes 6 tools (definition, references, diagnostics, hover, rename_symbol, edit_file) that work correctly with real language servers across Go, Python, TypeScript, and Rust codebases.
What the agent ended up with on a clean machine, in its own words. How this is measured
Measured by Argusic on a fresh machine every time. Every number links to its evidence. Argusic Score 93.3 of 100 (the mean of this project's run scores).
At a glance
Subject data from GitHub, linked at the top of this page, refreshed . Test data by Argusic (CC BY 4.0); every number links to a run page with the full log, the recording, and their sha256 hashes.
What was measured
From the run that decided this verdict. Every line is a recorded value, not an estimate.
What went wrong, in the agent's own words
The agent's own words, worst first, never rewritten into advice.
- Watcher tests had race condition: events channel not drained on ResetEvents, causing stale signals5 minutes
- Go not installed3 minutes
- Go hover snapshots mismatched (gopls v0.23.0 outputs different struct size format)2 minutes
- Python hover snapshots mismatched (pyright 1.1.414 outputs different hover format)2 minutes
- Rust integration test snapshots mismatched (rust-analyzer 1.99.0)2 minutes
- TypeScript tests failed: typescript-language-server requires TypeScript installed in workspace1 minute
- Install time
- 67 minutes
- Cold machine to finish
- 62 minutes
- Errors hit and fixed
- 9 hit, 6 fixed with no human help
- How the result was proved
- Binary builds and responds to MCP initialize: echo '{"jsonrpc":"2.0","id":1,"method":"initialize"...}' | timeout 15 /tmp/mcp-language-server --workspace /tmp/test-workspace --lsp gopls returned valid MCP initialize response with protocolVersion. Test suites ran successfully against real gopls, pyright, typescript-language-server, and rust-analyzer, 7 Go suites passed, 5 Python suites passed, 5 TypeScript suites passed, Rust definition/hover/references/rename_symbol passed. Internal watcher and tool tests passed.
- Model tokens used
- 564,055
- Exact commit tested
- e4395849a52e
- Container image
- sha256:cdd920bce783
What was not measured
The other half, so you can see exactly how far this evidence goes. A gap is printed as a gap and never filled in.
- Peak GPU memory
- this ran on a CPU machine, so there was no GPU to sample
- Behaviour over a long run
- each attempt uses the smallest documented settings and a fixed time budget, so this measures whether it runs, not how it holds up under load
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
All tests that work with available dependencies pass reliably. The only remaining failures are: - `clangd/` — no clangd binary in the container (expected, C/C++ tools not available) - `rust/diagnostics/FileDependency` — timing-dependent test that requires faster rust-analyzer resp… - `rust/references/helper_function` — the same indexing timing issue These are all pre-existing timing/availability issues, not code defects. tokens used 564,055 All tests that work with available dependencies pass reliably. The only remaining failures are: - `clangd/` — no clangd binary in the container (expected, C/C++ tools not available) - `rust/diagnostics/FileDependency` — timing-dependent test that requires faster rust-analyzer resp… - `rust/references/helper_function` — the same indexing timing issue These are all pre-existing timing/availability issues, not code defects.
Replay the whole session, every command from a clean machine to this point.
How it was tested
One agent, one container, no human help. It installs the project the way its own documentation says to, runs it, and fixes what breaks. Everything below is recorded as it happened: the terminal session, the log and the exact commit. The full method.
Strengths and limits
Measured facts, not opinions. How this is written.
What went well
- Reached a running state on a clean machine, with the session recorded.
- Ran without a GPU, so it does not need one to start.
- Licensed BSD-3-Clause, as reported by its host.
What did not, or is not known
- Took 67 minutes to install, slower than the median of the 99 comparable projects Argusic has measured.
- Hit 9 errors during setup, 3 of which were not solved.
- Measured once so far. A single attempt shows it can run, not that it runs reliably.
Of the 100 ai projects Argusic has installed and timed, mcp-language-server was the 99th fastest to reach a running state, and 69 of 100 reached one at all.
What it is a reasonable choice for
- Trying it on a laptop or a small server: it reached a running state without a GPU.
Also tested, in the same area
Every one of these was installed and run by Argusic on a clean machine. Nothing appears here that was not tested.
Run history
Topics (from GitHub)
ailanguage-server-protocolmcpmcp-servermodel-context-protocol
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/mcp-language-server)Questions
- Does mcp-language-server run?
- Yes. mcp-language-server runs. Argusic installed and launched it on a clean machine in 67 minutes, hitting 9 errors on the way, and recorded the session.
- How did Argusic test mcp-language-server?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit e4395849a52e. One attempt is recorded, and the full method is on the methodology page.
- What did it cost to test mcp-language-server?
- The run that produced this verdict cost $0.21: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does mcp-language-server take to install?
- 67 minutes in the run that decided this verdict, from a clean machine to a running state. That is one measured attempt, not an average.
- Does mcp-language-server need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing mcp-language-server?
- 9 things broke in the recorded run, and 6 were fixed without human help. Each one, and the time it cost, is listed on this page.
- How does mcp-language-server compare with the alternatives?
- Of the 100 ai projects Argusic has installed and timed, mcp-language-server was the 99th fastest to reach a running state, and 69 of 100 reached one at all.
- Where is the evidence for mcp-language-server?
- The recorded run is on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.