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Route LLM queries over MCP by cost, policy, and verification logic.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "llm-routing" yet — see the docs or source repo.
Route this user query to the most suitable LLM using a cost-first policy, and explain the choice with an estimated cost.
Returns a recommended routing decision, the policy rationale, and an approximate cost estimate for the request.
Resume the previously paused routing task that required escalated approval, and report the current status and next recommended step.
Returns the resumed approval or routing status and explains the next available action.
Compare the differences between a 'lowest-cost first' policy and a 'higher-verification first' policy for this type of query.
Outputs policy differences, likely model choices, and the trade-offs between cost and reliability.
Developers using multiple LLMs can automatically choose an appropriate model based on cost and policy instead of always calling the most expensive one. It can also estimate costs to help optimize budgets.
When certain requests require higher confidence or extra checks, verification-based cascading can progressively escalate handling. This helps balance cost and reliability.
Ops teams or researchers can inspect routing explanations, compare policies, and use read-only resources to understand current behavior or configuration. This makes auditing and tuning routing rules easier.
It performs cost-aware LLM routing over MCP and supports verification-based cascading. It also offers tools for routing queries, resuming escalated approvals, estimating costs, comparing policies, and explaining routing decisions.
It does more than routing. Based on the description, it also includes read-only resources and a policy-selection prompt to help users understand and choose routing policies.
The provided material does not include installation steps, runtime requirements, or key information. See the source repository for details.
Route prompts across LLM providers with policy-based orchestration and verification.
Route LLM requests across providers and orchestrate MCP tools with local privacy.
Route LLM tasks locally first to keep sensitive data private and controlled.
Aggregate MCP servers and route tools intelligently for efficient parallel work.
Discover AI models, pricing, and chat completions through RouterBase.
Access AI engineering roadmaps, projects, and certifications from MCP clients.