letta-ai/letta-code is an agent harness for building assistants that retain memory, identity, and experience across interactions instead of treating each task as isolated. Developers use it through local, desktop, browser, or messaging interfaces for interactive or continuously running agents, and its catalogue entries configure the agents' skills, instructions, rules, and behavior.
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 agentmods add skills/letta-ai/letta-code/using-mcp-toolsnpx skills add letta-ai/letta-code --skill using-mcp-toolsgit clone --depth 1 https://github.com/letta-ai/letta-codeWrote 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/letta-ai/letta-code/using-mcp-tools)<a href="https://agentmods.dev/skills/letta-ai/letta-code/using-mcp-tools"><img src="https://agentmods.dev/badge/skills/letta-ai/letta-code/using-mcp-tools.svg" alt="Measured on agentmods" 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 | $0.00079 | $0.00841 |
| Opus 5 | $0.00039 | $0.00420 |
| Sonnet 5 | $0.00016 | $0.00168 |
| Haiku 4.5 | $0.00008 | $0.00084 |
Grade A, and why
using-mcp-tools 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 2d 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 — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Using MCP tools
letta mcp gives the agent one unified view of every MCP server it can reach: servers connected to the agent in Letta Cloud and servers configured locally on this machine. It works from any surface where the agent runs — cloud sandboxes (chat.letta.com), Letta Desktop, and terminals. All output is JSON.
Commands
letta mcp list # servers: [{name, transport}]
letta mcp get <server> # one server's connection configuration (credentials redacted)
letta mcp tools [server] # tool names + descriptions only
letta mcp tools [server] --full # ...including every tool's complete schema
letta mcp schema <tool-name> # one tool's complete schema
letta mcp search <query> [--mode] [--limit] # ranked tool schemas: [{tool, rank, score}]
letta mcp call <tool-name> [--args | --args-file] # run a tool, print a CallToolResult
Every command accepts --agent <id>, defaulting to LETTA_AGENT_ID/AGENT_ID — do not pass it unless targeting another agent.
Search options
--mode <hybrid|vector|fts>— defaulthybrid.vectoruses server-side embeddings and covers only cloud-connected servers;ftsandhybridalso rank local tools lexically. Agents on a local backend cannot usevector.--limit <n>— result count, 1-100 (default 5).- Rank order is meaningful; absolute scores are not comparable across queries. When even the top results look unrelated to the query, no relevant tool likely exists — do not force the best-ranked one.
Call arguments and results
--args '<json>'— inline JSON object.--args-file <path>— read the JSON object from a file;--args-file -reads stdin. Use these for large or shell-quoting-hostile payloads.- Output is an MCP CallToolResult:
content(array of typed blocks), optionalstructuredContent, andisError. - Exit codes:
0success,1CLI/usage error (JSON on stderr:{error: {code, message, hint?}}),2the tool ran and returned an error result — readcontentfor the server's message, fix the arguments, and retry. - Summarize relevant results instead of pasting large raw payloads.
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.
- 2d ago First seen · 45 lines · 79 tokens per session scan A 31f2083652c1
using-mcp-tools is a skill published in the GitHub repository letta-ai/letta-code (3,193 stars, last pushed today), licensed Apache-2.0. It adds 79 tokens to every session and 841 once invoked, about $0.0004 per session on Opus 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 2026-09-02.
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