@rotifer/mcp-server

Build, compose, and run AI agents — directly from your IDE.

Search genes, create agents with composable genomes, run pipelines in a WASM sandbox, and compete in the Arena. Zero config. Works with Cursor, Claude Desktop, Windsurf, and any MCP-compatible client.

{ "mcpServers": { "rotifer": { "command": "npx", "args": ["@rotifer/mcp-server"] } } }

{ "mcpServers": { "rotifer": { "command": "npx", "args": ["@rotifer/mcp-server"] } } }

Use the samenpxcommand — any client that supports MCP stdio transport will work.

Create and run an agent in one conversation

You: "Build me an agent for code security scanning" AI: → create_agent({ agent_name: "sec-bot", gene_ids: ["security-scanner", "genesis-code-format"], composition: "Seq" }) Agent 'sec-bot' created with 2-gene Seq genome. You: "Run it on my project" AI: → agent_run({ agent_name: "sec-bot", input: "{\"path\":\"./src\"}" }) Pipeline complete — 3 findings, 0 critical.

You: "Find the best gene for web search" AI: → search_genes({ query: "web search" }) Found 8 genes. Top match: genesis-web-search (F(g) = 0.87, Native) You: "Compare it against the lite version" AI: → compare_genes({ gene_ids: ["...", "..."] }) Side-by-side: success rate, latency, fitness breakdown

You: "Wrap my function as a gene" AI: → wrap_gene({ gene_name: "my-search", domain: "search.web", fidelity: "Wrapped" }) → compile_gene({ gene_name: "my-search" }) → test_gene({ gene_name: "my-search", compliance: true }) → publish_gene({ gene_name: "my-search", changelog: "Initial release" })

MCP Resources let AI clients reference Rotifer data as context:

Each resource returns what the tool of the same job returns, so a declared tool set covers both: with--tools=evolve,rotifer://genes/{gene_id}/stats,rotifer://developers/{username}androtifer://leaderboarddisappear from the listing and are refused if read directly, becauseget_gene_stats,get_developer_profileandget_leaderboardwere not asked for.rotifer://versionalways answers — it is the server describing itself, not a capability. Before 0.16.0 these were reachable whatever the tool set said.

MCP Prompts give AI clients guided workflows for common tasks:

Try asking your AI:"Use the rotifer-hello prompt to build me an agent"or"Use rotifer-architect to design an agent for document Q&A".

┌─────────────────────────────────────────────────┐ │ AI IDE (Cursor / Claude / Windsurf) │ │ │ │ "Find genes for code formatting" │ │ │ │ │ ▼ │ │ ┌─────────────────────┐ │ │ │ MCP Client │ │ │ │ (stdio transport) │ │ │ └────────┬────────────┘ │ └───────────┼─────────────────────────────────────┘ │ MCP Protocol ▼ ┌─────────────────────────────────────────────────┐ │ @rotifer/mcp-server │ │ │ │ 30 Tools 7 Resources 4 Prompts Local Scanner│ │ ┌──────────┐ ┌───────────┐ ┌────────────┐ │ │ │ discover │ │rotifer:// │ │ ./genes/ │ │ │ │ lifecycle│ │genes/stats│ │ phenotype │ │ │ │ agents │ │developers │ │ agents │ │ │ │ auth │ │leaderboard│ └────────────┘ │ │ └────┬─────┘ └─────┬─────┘ │ │ └───────┼──────────────┼────────────────┼─────────┘ │ │ │ ▼ ▼ ▼ ┌─────────────────────────────────────────────────┐ │ Rotifer Cloud API Local File System │ │ (Supabase) (genes/, .rotifer/) │ └─────────────────────────────────────────────────┘

Zero-config by default — connects to the public Rotifer Cloud API.

To use a custom endpoint, create~/.rotifer/cloud.json:

{ "endpoint": "https://your-supabase-instance.supabase.co", "anonKey": "your-anon-key" }

ROTIFER_CLOUD_ENDPOINT=https://your-instance.supabase.co ROTIFER_CLOUD_ANON_KEY=your-anon-key

All thirty-one tools are available by default.ROTIFER_MCP_TOOLSnarrows that to what a given integration actually needs — useful when the server is attached to an assistant that should not be able to publish or log in on your behalf:

npx @rotifer/mcp-server --tools=evolve # the rank-and-swap preset (10 tools) npx @rotifer/mcp-server --tools=readonly # nothing that writes (14 tools) ROTIFER_MCP_TOOLS=search_genes,get_gene_detail # an exact list ROTIFER_MCP_TOOLS=evolve,vg_scan # a preset plus one

The flag and the variable do the same thing, and the flag wins if both are set. Both exist because callers differ in what they can reach: a shell user sets the variable, while something launching this server from a manifest controls only the command line.

A declared set covers the whole surface, not justtools/list. Tools outside it are refused when called by name;resourcesthat duplicate an excluded tool are dropped from the listing and refused when read; and the sandbox escape hatches below stay off unless separately declared. A restriction with an unlisted way around it is not a restriction.

npx @rotifer/mcp-server --allow=no-sandbox npx @rotifer/mcp-server --allow=no-sandbox,trust-unsigned ROTIFER_MCP_ALLOW=no-sandbox # same thing

rotifer agent run <name> --no-sandbox rotifer run <gene> --trust-unsigned

rollback_gene {} → what can be rolled back rollback_gene { gene_name: "formatter" } → restore the copy that was replaced

ROTIFER_TELEMETRY=0 # also accepts false / off

The three arelogMcpCall,logGeneInvocationand thetrack_downloadcall insideinstallGene, all insrc/cloud.ts— short enough to read in full. Nothing else here reports anything on its own: every other outbound call in this server is a tool you invoked doing its job — a query, a publish, a sign-in — plus the WASM artifact download and one npm version check per day.

This MCP server works best alongside theRotifer CLI. The CLI provides the local runtime (WASM sandbox, Arena engine, IR compiler) while the MCP server exposes it all to your AI assistant:

npm install -g @rotifer/playground rotifer init my-agent && cd my-agent rotifer hello --template quality-advisor # your first Agent workspace in seconds

- Rotifer Protocol— Main site
- MCP Setup Guide— Step-by-step setup
- Gene Marketplace— Browse and discover Genes
- CLI Playground— Build and test Genes locally
- Protocol Specification— Formal spec

An MCP server for initial app planning and creating a good starting point for an app.