Tool Discovery. Context Compression. Parallel Execution. Smart Caching.
The MCP Scalability Problem
Your agent pays the price.
Your agent doesn't need 10,000 tools. It only needs the right one.
Stop sending 50,000 rows into your context window.
Run MCP tools in parallel. Not one by one.
Stop repeating expensive tool calls from scratch.
The Solution
Sits between your agent and MCP servers. Handles discovery, compression, caching, and orchestration.
Search tools by intent. Load only what matters.
Prevent oversized tool outputs from polluting context.
Large responses saved as files. Agents receive metadata instead.
Reuse expensive tool calls automatically.
Run independent tool calls concurrently.
Architecture
See The Difference
{
"rows": 500000
}
// 500,000 rows dumped
// into agent context
// Token cost: ~$2.50
// Window: nearly full{
"file": "query.parquet",
"rows": 500000,
"summary":"Top 10 customers..."
}
// Metadata only in context
// Full data on disk
// Token cost: ~$0.01
// Agent stays focusedFAQ
AnyMCP is the MCP Runtime Layer that sits between your agent and MCP servers, providing tool discovery, context compression, parallel execution, and smart caching.
AnyMCP's Context Firewall automatically compresses or materializes large tool responses. Your agent gets summaries instead of raw data, keeping context windows clean.
Yes, AnyMCP is open source and free to use. Cloud and Enterprise tiers are planned for future release.
No. AnyMCP works with any existing MCP server without modifications. It wraps standard MCP connections and adds runtime capabilities transparently.
Large responses are automatically written to disk as Parquet, CSV, or JSONL files. The agent receives only the schema, summary, and file path.
Blog
Dynamic discovery keeps context lean and selection fast.
Compression and materialization protect your agent's reasoning.
Parallelize execution and cut response times by 3x.
Protocol vs runtime — and why the distinction matters.
The next frontier for agent infrastructure.
Be the first to know when AnyMCP launches. Join the waitlist for early access.