How long does the integration take?

Change one base URL in an OpenAI-compatible client, or install the Python or TypeScript SDK; the quickstart routes a first request in a few minutes.

Will this lock us into another vendor?

No. The router is Apache-2.0 open source, your provider keys stay yours, and the API is OpenAI-compatible, so leaving is a change of base URL.

What happens when a provider fails?

The router falls back to the next model your policy allows and records the fallback in the trace, so an outage costs a retry, not an incident.

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OpenSmartRoute

GenPark Adaptive Batch Request Debouncer - Tool - OpenSmartRoute

Toolv1.0.1

GenPark Adaptive Batch Request Debouncer

Name: GenPark Adaptive Batch Request Debouncer
Author: alphaparkinc

Adaptive sliding window query debouncing and micro-batch coalescing engine optimizing LLM throughput

by alphaparkinc(0) 0 installs

Free

Free account. Installing gives you the manifest plus copy-paste snippets.

See reviews

About

Imported from the official MCP registry - entry io.github.alphaparkinc/genpark-adaptive-batch-request-debouncer-skill v1.0.1. Ratings and installs below are from this marketplace.

GenPark Adaptive Batch Request Debouncer

Adaptive sliding window query debouncing and micro-batch coalescing engine optimizing LLM throughput

Packages

mcpb: https://github.com/Alpha-Park/genpark-adaptive-batch-request-debouncer-skill/releases/download/v1.0.1/genpark-adaptive-batch-request-debouncer-skill-v1.0.1.mcpb

Source: https://github.com/alphaparkinc/genpark-adaptive-batch-request-debouncer-skill

Registry entry: io.github.alphaparkinc/genpark-adaptive-batch-request-debouncer-skill

Use it

Copy one of these into your project. Installing also returns the manifest and these snippets.

# after Install: the listing is in your workspace's routing pool - nothing else to configure
curl -s -X POST https://api.opensmartroute.ai/api/v1/route -H 'Authorization: Bearer $OSR_API_KEY' -H 'Content-Type: application/json' -d '{"text": "...", "plan": true}'
# or pin it on the OpenAI-compatible endpoint: {"model": "mcp-io-github-alphaparkinc-genpark-adaptive-batch-reques-0fd4e7", ...}

Installed into a catalogue, chosen by a router

Install GenPark Adaptive Batch Request Debouncer and it becomes one more candidate the router can pick - when it fits.

A listing is a routing target with a manifest: what it does, which domains it covers, what it costs and who publishes it. Once installed it sits beside your own models and tools, is scored like any other candidate for each request, and shows up in the trace when it wins. Ratings come from workspaces that installed it, one per account.

Photo: RDNE Stock project

For the business

What it costs to adopt - in engineering time.

Same client, same code
One base URL
The OpenAI-compatible endpoint answers your existing SDK calls; model=auto lets the router choose.
The SDKs
One URL, every vendor
No vendor lock-in
Point your OpenAI-compatible client at one address; add, swap or retire providers in the catalogue without touching application code.
Every vendor side by side
Next eligible model answers
Failover built in
When a provider is down or over quota the request moves on; the trace says it did.

Manifest

An Open Capability Manifest: the router reads it to know what this does, what it costs and when to pick it.

mcp-io-github-alphaparkinc-genpark-adaptive-batch-reques-0fd4e7.ocm.jsonjson

{
  "ocm": "1",
  "id": "mcp-io-github-alphaparkinc-genpark-adaptive-batch-reques-0fd4e7",
  "kind": "tool",
  "name": "GenPark Adaptive Batch Request Debouncer",
  "description": "Adaptive sliding window query debouncing and micro-batch coalescing engine optimizing LLM throughput",
  "publisher": "alphaparkinc",
  "version": "1.0.1",
  "capabilities": {
    "domains": [
      "data_analysis",
      "math"
    ],
    "tags": [
      "mcp",
      "mcp-server",
      "mcpb",
      "mcp-registry"
    ],
    "languages": [
      "en"
    ]
  },
  "quality_prior": 0.6,
  "examples": [
    "Adaptive sliding window query debouncing and micro-batch coalescing engine optimizing LLM throughput"
  ],
  "primary": false,
  "metadata": {
    "source": {
      "provider": "mcp-registry",
      "repository": "https://github.com/alphaparkinc/genpark-adaptive-batch-request-debouncer-skill",
      "path": "server.json",
      "ref": "1.0.1",
      "url": "https://github.com/alphaparkinc/genpark-adaptive-batch-request-debouncer-skill",
      "key": "io.github.alphaparkinc/genpark-adaptive-batch-request-debouncer-skill",
      "registry": "https://registry.modelcontextprotocol.io"
    }
  }
}

Fetch it by URL: GET /api/v1/registry/mcp-io-github-alphaparkinc-genpark-adaptive-batch-reques-0fd4e7/manifest?version=1.0.1

About

GenPark Adaptive Batch Request Debouncer

Packages

Use it

Install GenPark Adaptive Batch Request Debouncer and it becomes one more candidate the router can pick - when it fits.

What it costs to adopt - in engineering time.

One base URL

No vendor lock-in

Failover built in

Manifest

Reviews