Computase
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Computase Translate the sequence ATGGCCTAA"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Computase
Computase is a local Python library for small, well-defined DNA and RNA sequence calculations:
nucleotide composition, GC bounds, and GC skew
DNA or RNA reverse complements
translation with selectable NCBI genetic-code tables
six-frame candidate ORF enumeration
IUPAC motif searches on either strand
The Python API is the primary interface. The same operations are also available through the optional Model Context Protocol (MCP) interface for local agent workflows. Computation runs locally; input sequences are not sent to a service.
Install
For most Python environments:
pip install computaseFor a project managed with uv:
uv add computasePython 3.11 or newer is required.
Related MCP server: mcp-ensembl
Quick start
from computase.seq import translate_sequence
sequence = ">synthetic-cds\nATGGCCATTGTAATGGGCCGCTGAAAGGGTGCCCGATAG\n"
result = translate_sequence(sequence, table_id=1)
print(result.model_dump())Representative output (computase_version matches the installed release):
{'computase_version': '<installed version>', 'parameters': {'table_id': 1, 'stop_handling': 'translate-through'}, 'protein': 'MAIVMGR*KGAR*', 'table_id': 1, 'table_name': 'Standard', 'stop_handling': 'translate-through', 'codon_count': 13, 'stopped_early': False}Results are typed Pydantic models. They record the Computase version and effective parameters, but never echo the full input sequence.
See the Python examples for concise, runnable examples of all five sequence operations.
Capabilities and validation
Scientific task | Python function | Contract and validation evidence |
Composition, GC content bounds, and GC skew |
| Preserves IUPAC uncertainty; checked against the GenBank HBB coding sequence and composition/property invariants |
DNA/RNA reverse complement |
| Preserves the input alphabet and IUPAC symbols; checked against an M13 reference sequence and the reverse-complement involution property |
NCBI genetic-code translation |
| Uses a selected NCBI table and requires complete codons; checked against an NCBI translation example and table-specific codons |
Six-frame candidate ORF enumeration |
| Reports forward-reference coordinates and explicit start, stop, and nesting policies; checked with synthetic fixtures spanning all six frames and coordinate round trips |
IUPAC motif search |
| Supports ambiguous symbols, overlapping matches, and either strand; checked against the pUC19 EcoRI site and interval/property tests |
These checks establish the documented conventions and regression boundaries; they do not establish correctness for every biological interpretation or use case. If a result differs from an independent reference, use the scientific correctness report with a minimized, non-sensitive sequence.
Scientific scope and conventions
Inputs are raw nucleotide strings or a single FASTA record, not multi-record files.
Coordinates are 0-based and end-exclusive on the normalized forward reference, after FASTA headers and whitespace are removed.
Strand is reported separately;
normalized_sequence[start:end]reproduces each reported forward span.ORFs are sequence candidates, not gene predictions.
IUPAC GC bounds preserve uncertainty rather than assigning probabilities.
Sequence length is capped at 5,000,000 nucleotides; motif and result limits are enforced.
Computase 0.1.x does not fetch records, align sequences, or annotate genes.
Optional MCP interface
stdio
With uv installed, uvx can run the MCP server without installing Computase
into the current environment:
{
"mcpServers": {
"computase": {
"command": "uvx",
"args": ["computase"]
}
}
}If Computase was installed with pip into an environment available to the MCP
client, use computase as the command and omit the arguments. For a uv-managed
project, run uv run computase from the project root; configure the MCP client
with uv as the command and ["run", "computase"] as the arguments.
The five tools are computase_summarize_sequence, computase_reverse_complement, computase_translate_sequence, computase_enumerate_orfs, and computase_scan_motif.
Streamable HTTP
uvx computase --transport streamable-http --host 127.0.0.1 --port 8000Connect an MCP client to http://127.0.0.1:8000/mcp. HTTP binds to localhost by default.
Do not expose the Computase HTTP server directly to a public network. Non-loopback deployment requires a separately managed TLS boundary that authenticates every request and enforces request-size, concurrency, and rate limits.
Companion Skill
The repository and source distribution include a
Computase companion Skill
that teaches agents when and how to choose the five operations. Prefer the
Computase MCP tools when configured; otherwise the Skill can run an isolated
uv fallback that resolves Computase without mutating the active environment.
Its
usage examples
cover MCP, runner, and Python workflows. These Skill files are not installed by
the Python wheel.
Install the Skill into a supported agent with:
npx skills add madhusudan-kulkarni/computase --skill computaseskills.sh indexes public repositories from install telemetry. There is no separate submission form.
Development
Use uv sync --locked --extra dev, then run:
uv lock --check
uv run --locked ruff format --check src tests evaluations scripts skills/computase/scripts
uv run --locked ruff check src tests evaluations scripts skills/computase/scripts
uv run --locked mypy src tests evaluations scripts skills/computase/scripts
uv run --locked pytest -q
uv run --locked python -m evaluations.runnerSee CONTRIBUTING.md for reference-vector requirements.
Roadmap
See ROADMAP.md for planned capabilities, including melting temperature calculations, restriction digestions, and a client-side WebAssembly interface.
Citation
If Computase contributes to your work, cite the software metadata in CITATION.cff. GitHub also exposes this through Cite this repository. Computase is also registered on bio.tools.
License
Computase is licensed under the MIT License.
Available Tools
5 toolscomputase_enumerate_orfsEnumerate candidate ORFsARead-onlyIdempotent
Enumerate bounded candidate ORFs across all six reading frames.
Inputs: sequence (required), table_id, max_results, require_stop, +3 more. Returns: Bounded collection of candidate open reading frames.
computase_reverse_complementReverse complementARead-onlyIdempotent
Compute an IUPAC-aware DNA or RNA reverse complement.
Inputs: sequence (required). Returns: Reverse complement of a nucleotide sequence.
computase_scan_motifScan motifARead-onlyIdempotent
Scan an IUPAC motif on the forward, reverse, or both strands.
Inputs: motif (required), sequence (required), strand, max_matches, +1 more. Returns: Bounded motif scan result.
computase_summarize_sequenceSummarize sequenceARead-onlyIdempotent
Summarize composition, GC uncertainty, and GC skew.
Inputs: sequence (required). Returns: Composition and GC metrics for a nucleotide sequence.
computase_translate_sequenceTranslate sequenceARead-onlyIdempotent
Translate complete codons with a selected NCBI genetic code.
Inputs: sequence (required), table_id, stop_handling. Returns: Protein translation under an NCBI genetic code.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 5 tools
Each tool targets a distinct operation: summarization, reverse complement, translation, ORF enumeration, and motif scanning. There is no functional overlap or ambiguity between them.
All tools follow a consistent snake_case verb_noun pattern with the same computase_ prefix. The naming is uniform and predictable across the entire set.
Five tools form a compact, purposeful toolkit for common sequence analysis tasks. Each tool adds meaningful capability without bloat or triviality.
The server covers core sequence manipulation and analysis workflows: composition stats, complementing, translation, ORF detection, and motif scanning. Minor gaps such as restriction enzyme analysis or format conversion exist, but the main stated domain is well served.
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