Genomic Intelligence

find_genes_and_predict_expression

Find genes in a sequence, then predict each gene's expression (composite).

    Server-side chaining in ONE call: finds genes (transcript intervals,
    with their TSS) in the sequence, then predicts expression off each
    discovered TSS in the given experimental context. This is the right
    tool whenever you want expression for a raw region or sequence — e.g.
    "find the genes in chr8:… and predict their expression in K562".
    predict_expression scores the sequence around ONE TSS and needs you to
    know where that TSS is (a 9,198 bp window with the TSS at its
    midpoint, or a longer sequence plus `tss_index`); this tool discovers
    every gene's TSS itself. It has no 9,198 bp floor and no tss_index;
    it starts with gene finding, so it takes 1,000–500,000 bp.

    Runs async internally at every size (the annotate stage is slow even
    for small inputs), so progress always streams. With wait=True
    (default), blocks and streams progress, then returns the result
    {data, meta} — it never returns a job_id on this path. With wait=False
    (detached), returns {data: {job_id, status: 'submitted'}} immediately —
    poll it with get_job. Because it ends in expression, `description`
    (cell type / assay context) is REQUIRED.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`wait`	No	Default True: block and stream progress until the result is ready. Set False for detached mode — returns a job_id immediately to poll with get_job.
`sequence`	No	DNA bases, 1,000-500,000 bp (line breaks ignored). Mutually exclusive with sequence_ref.
`description`	No	REQUIRED experimental context — cell type / assay / conditions (e.g. 'K562 cell line'), applied to every found gene. The workflow ends in expression, which the API rejects without it.
`sequence_ref`	No	Stored sequence handle. Mutually exclusive with sequence.
`sequence_name`	No	Label echoed back.	sequence

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedAug 19, 2026

changedInput schema / properties / sequence / description

Previous value: -"DNA bases. Mutually exclusive with sequence_ref."New value: +"DNA bases, 1,000-500,000 bp (line breaks ignored). Mutually exclusive with sequence_ref."

First observedJul 27, 2026

TDQS

A4.6/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the annotations (readOnlyHint=false, openWorldHint=true, idempotent=false), the description discloses async-internally execution, that progress always streams, the two return shapes for wait=True vs wait=False, and the 1,000-500,000 bp range with no bp floor or tss_index. It could add more on failure/timeout behavior, but this is well above the annotation baseline.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the purpose and the routing decision, then the mechanics; dense and mostly waste-free. Some of the wait-mode explanation repeats the parameter schema, which is slight redundancy but not padding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a composite async tool with 5 params and an output schema, the description covers the chaining model, the async/wait contract, the required context param, and the size envelope. An agent has everything needed to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so 3 is the floor; the description earns above that by clarifying that `description` is REQUIRED (the schema lists no required params) and by explaining wait=True/False semantics and the mutual exclusivity constraints of sequence/sequence_ref.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific two-stage verb phrase (find genes, then predict expression) and labels itself a composite. It explicitly contrasts with the sibling predict_expression and find_genes, so an agent can route without opening schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit when-to-use rule ('the right tool whenever you want expression for a raw region or sequence') plus a concrete example, and names the alternative and its precondition (predict_expression needs the TSS location and a 9,198 bp window). Nothing is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Genomic Intelligence tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?