SynthesizeBio MCP

Live

OAUTH 2.0

AI

AI

Connect to SynthesizeBio MCP to query biological research databases, run compound analyses, and retrieve scientific insights for life-science AI workflows.

  • Acts as the user: Every tool call runs as the authorizing user. Access and audit trail stay intact.
  • Credentials stay vaulted: AES-256 encrypted, resolved at request time, never stored in LLM context.
  • Scoped before every call: Per-user permissions enforced automatically. 90-day audit trail included.
SynthesizeBio MCP
agent · Acme Q3
Run
Analyze Gene Expression in Synthesize Bio MCP
S
synthesizebiomcp_analyze_gene_expression
85ms
Synthesize Bio MCP agent
Start a differential gene expression analysis using synthesize bio's ai platform, returning a job id to track progress..
Sources: Synthesize Bio MCP
synthesizebiomcpmcp
1 tool call
18:29
Message Claude...

SynthesizeBio MCP tools for AI agents

CALL ANY TOOL
6 tools covering search, analyze, get.
synthesizebiomcp_analyze_gene_expression
Start a differential gene expression analysis using synthesi
Start a differential gene expression analysis using synthesize bio's ai platform, returning a job id to track progress.
Parameters
Name
Type
Required
Description
resolution_id
string
Required
The completed resolution_id returned by resolve_sample_metadata.
synthesizebiomcp_get_analysis_results
Poll the status and results of a running gene expression ana
synthesizebiomcp_get_counts_data_url
Retrieve a presigned download url for the raw gene expressio
synthesizebiomcp_resolve_sample_metadata
Resolve a natural-language experiment description into struc
Build your Agent
Same auth pattern across every framework.
Python · LlamaIndex
from langchain_mcp_adapters.client import MultiServerMCPClient
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="synthesizebiomcp")

mcp = MultiServerMCPClient({
"synthesizebiomcp": {
"url": "https://mcp.scalekit.com/synthesizebiomcp",
"headers": {"Authorization": "Bearer " + token}
}
})
tools = await mcp.get_tools()
import OpenAI from "openai";
import { ScalekitClient } from "@scalekit-sdk/node";

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "synthesizebiomcp" });

const openai = new OpenAI();
// Connect to MCP at https://mcp.scalekit.com/synthesizebiomcp
// Pass: Authorization: Bearer + token
import Anthropic from "@anthropic-ai/sdk";
import { ScalekitClient } from "@scalekit-sdk/node";

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "synthesizebiomcp" });

const anthropic = new Anthropic();
// Connect to MCP at https://mcp.scalekit.com/synthesizebiomcp
// Pass: Authorization: Bearer + token
from google.adk.agents import LlmAgent
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="synthesizebiomcp")
# Connect to MCP at https://mcp.scalekit.com/synthesizebiomcp
# Pass: Authorization: Bearer + token
Try these prompts
Paste any prompt into your agent to get started.
Get started
Copy the prompt
Copied
Resolve a natural-language experiment description into structured sample groups using Synthesize Bio’s AI metadata extra?
Copy the prompt
Copied
Retrieve a presigned download URL for the raw gene expression counts data produced by a completed analysis job?
Advanced
Copy the prompt
Copied
Start a differential gene expression analysis using Synthesize Bio’s AI platform, returning a job ID to track progress?
SEE HOW AUTH WORKS
User authorises once. Every agent call after uses their token with scope enforcement.
1
Authorize
Your user connects
SynthesizeBio MCP
once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access
Who:
user ‘A’
when:
Once per user
access:
Limited to user
2
Store
Their
SynthesizeBio MCP
token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection
vault:
encrypted
scope:
per-user
tokens:
auto-refreshed
3
Resolve
When your agent calls a
SynthesizeBio MCP
tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs
speed:
~40ms
check:
before every call
seen by:
nobody
4
Audit
Every
SynthesizeBio MCP
tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it
history:
90 days
export:
SIEM-ready
logged:
every call
Test other agents
See the same per-user auth pattern across other connectors.
No items found.
Why Scalekit
Secure your agent's access. Connectors ship in minutes
Other connector libraries treat auth as a demo afterthought.
01.
Shared tokens break per-user analytics
A shared token looks fine in a demo. In production every call looks like a service account. Scalekit resolves the real user credential.
// shared token
audit → bot_service_account

// scalekit
audit → user_abc ✓
02.
Authentication is not authorization
03.
Multi-tenancy is architectural
04.
One connector today. Ten tomorrow.
“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”
Venu Madhav Kattagoni
Head of Engineering / Von
FAQs
Frequently Asked Questions

Does the agent access SynthesizeBio as the user or as a shared key?
As the user. Each workspace member authorizes once and Scalekit resolves their credential at request time. Audit logs attribute every action to that user, not a shared service account.

Where is the SynthesizeBio OAuth token stored?
In Scalekit's managed AES-256 token vault, namespaced per tenant. Refresh is automatic. Revocation is a single dashboard action. Tokens never appear in prompts, logs, or LLM context.

Can I limit what the agent is allowed to do in SynthesizeBio?
Yes. Pass a tool name filter to listScopedTools so the AI agent only sees the subset you authorize. Pre-API-call scope checks block out-of-policy actions before the request reaches SynthesizeBio.

What happens when a user revokes SynthesizeBio access?
The connection is invalidated on the next tool call. Subsequent requests for that user fail closed with a clear error. Other users in the tenant remain unaffected. The event is logged for audit.

Who can see gene expression analysis results?
Only the authorizing user who ran the analysis. Result retrieval and raw counts downloads use that user's Synthesize Bio credential, keeping research data isolated per scientist.

Start in your coding agent
Up and running in one command
Install the Scalekit skill in your editor of choice. Connector, auth, tools, prompt, all wired up
Claude Code REPL
/plugin marketplace add scalekit-inc/claude-code-authstack
/plugin install agentkit@scalekit-auth-stack
Cursor Code REPL
# ~/.cursor/mcp.json
{
""mcpServers"": {
""synthesizebiomcp"": {
""url"": ""https://mcp.scalekit.com/synthesizebiomcp"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}
Codex Code REPL
# ~/.codex/config.toml
[mcp_servers.synthesizebiomcp]
url = ""https://mcp.scalekit.com/synthesizebiomcp""
auth_env = ""SCALEKIT_TOKEN""
Copilot Code REPL
# .vscode/mcp.json
{
""servers"": {
""synthesizebiomcp"": {
""url"": ""https://mcp.scalekit.com/synthesizebiomcp"",
""type"": ""http""
}
}
}