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.
git clone --depth 1 https://github.com/religa/multi_mcpWrote 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/commands/religa/multi_mcp/multi-update-models)<a href="https://agentmods.dev/commands/religa/multi_mcp/multi-update-models"><img src="https://agentmods.dev/badge/commands/religa/multi_mcp/multi-update-models/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/commands/religa/multi_mcp/multi-update-models"><img src="https://agentmods.dev/badge/commands/religa/multi_mcp/multi-update-models.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 | $0.00000 | $0.00910 |
| Opus 5.5 | $0.00000 | $0.00364 |
| Sonnet 5.5 | $0.00000 | $0.00182 |
| Haiku 4.5 | $0.00000 | $0.00091 |
Grade A, and why
multi-update-models 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 1mo 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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Update Model Configuration
Research the latest available models from Anthropic, OpenAI, and Google, then update the project's model configuration accordingly.
Step 1: Read Current Config
Read the current model configuration:
multi_mcp/config/config.yaml- model definitions, aliases, constraintsmulti_mcp/settings.py- default model and default_model_list fallback
Note which models and aliases are already present.
Step 2: Research Latest Models
Use web search to find the latest available API models from each provider. Search the general web (e.g., "Anthropic latest Claude models API 2026", "OpenAI latest models API", "Google Gemini latest models API") in addition to checking provider docs. The doc URLs below are starting points but may become stale - always verify via general web search as well.
- Anthropic: Start with https://docs.anthropic.com/en/docs/about-claude/models - also search the web for latest Claude model announcements and API model IDs
- OpenAI: Start with https://platform.openai.com/docs/models - also search the web for latest GPT and o-series model announcements and API model IDs
- Google: Start with https://ai.google.dev/gemini-api/docs/models - also search the web for latest Gemini model announcements and API model IDs
For each provider, determine:
- New models not yet in config.yaml
- Models that have been deprecated or shut down
- Changes to existing model capabilities (context window, output tokens, etc.)
Step 3: Update Config
Edit multi_mcp/config/config.yaml:
- Add new models with appropriate
litellm_modelstrings (prefixed with provider:openai/,anthropic/,gemini/) - Remove models that have been shut down (not just deprecated - only remove if actually unavailable)
- Move aliases (like
mini,nano,gpt,sonnet,gemini) to point to the latest generation - Mark superseded models as legacy in their notes field
- Set
provider_web_search: truefor models that support it - Set temperature constraints (e.g.,
temperature: 1.0for GPT-5 family) - Keep the existing section structure (OpenAI, Azure, Anthropic, Google, CLI, Bedrock, OpenRouter)
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.
- 1mo ago First seen · 81 lines · 0 tokens per session scan A 48fc0542f7ea
multi-update-models is a command published in the GitHub repository religa/multi_mcp (36 stars, last pushed 5d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 910 tokens. 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 2026-08-30.
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