Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add xberg-io/liter-llm --skill liter-llm-using-the-mcp-servergit clone --depth 1 https://github.com/xberg-io/liter-llmWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/xberg-io/liter-llm/liter-llm-using-the-mcp-server)<a href="https://agentmods.dev/skills/xberg-io/liter-llm/liter-llm-using-the-mcp-server"><img src="https://agentmods.dev/badge/skills/xberg-io/liter-llm/liter-llm-using-the-mcp-server/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/xberg-io/liter-llm/liter-llm-using-the-mcp-server"><img src="https://agentmods.dev/badge/skills/xberg-io/liter-llm/liter-llm-using-the-mcp-server.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00044 | $0.00887 |
| Opus 5.5 | $0.00018 | $0.00355 |
| Sonnet 5.5 | $0.00009 | $0.00177 |
| Haiku 4.5 | $0.00004 | $0.00089 |
Grade A, and why
liter-llm-using-the-mcp-server scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Using the MCP Server
The liter-llm MCP server exposes 22 tools that mirror the proxy's REST
endpoints, so an MCP-compatible client (Claude Code, Claude Desktop) can call
174 LLM providers as tools with no glue code.
Standalone skill installation
Installing this skill alone does not register an MCP server or include the plugin launcher.
Install the CLI (for example, brew install xberg-io/tap/liter-llm), then configure your MCP client with
liter-llm mcp --transport stdio as its stdio command. The full product plugin supplies registration where
the runtime supports MCP.
How it runs in this plugin
The plugin auto-registers the server. Its command is the bundled launcher
scripts/mcp-launch.sh, which execs liter-llm mcp --transport stdio. On first
run the launcher resolves a liter-llm binary: it reuses one on PATH, then
tries npx/uvx, then Homebrew, then downloads a prebuilt
from the tool's latest GitHub release. Override with
LITER_LLM_LAUNCHER=auto|npx|uvx|brew|download.
To run it manually:
liter-llm mcp --transport stdio # for Claude Code / Claude Desktop
liter-llm mcp --transport http --port 3001
Configure model routing
Provider-backed tools use the proxy model registry. Create liter-llm-proxy.toml in the
working directory, or pass --config /absolute/path/liter-llm-proxy.toml when launching:
[[models]]
name = "gpt-4o"
provider_model = "openai/gpt-4o"
Supply OPENAI_API_KEY in the MCP process environment, then call chat using the
configured name gpt-4o. list_models shows configured names; an unknown model is a
request error. Missing credentials are also reported on provider-backed requests.
Gemini filters host credentials: install with --skip-settings and configure the selected
provider through gemini extensions config liter-llm "OpenAI key". Local stdio does not
need a separate proxy virtual key.
The 22 tools
Modality tools: chat, embed, generate_image, speech, transcribe,
moderate, rerank, search, ocr.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 91 lines · 44 tokens per session scan A 9a160fc044a5
liter-llm-using-the-mcp-server is a skill published in the GitHub repository xberg-io/liter-llm (261 stars, last pushed today), licensed MIT. It adds 44 tokens to every session and 887 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-15.
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