tcr-explorer 0.2.0

Federated TCR analysis: records retrieval, germline allele assignment, reconstruction, dossiers, and similarity, over a web UI, REST API, and MCP server

TCR Explorer

A federated tool for T cell receptor analysis. It retrieves known TCR records (VDJdb, IEDB, McPAS, TCR3d), assigns germline V and J genes down to the allele level, reconstructs full membrane bound chains, builds per receptor dossiers, and finds similar receptors. The same pure functions back a web UI, a REST API, and an MCP server, so an assistant can drive the whole tool.

How the data works

The package ships the IMGT germline (bundled under CC BY 4.0) but no record datasets. On first use you run tcr-explorer-refresh once. It downloads the four record datasets (VDJdb, IEDB, McPAS, TCR3d) from each source's own official endpoint into a local folder, then harmonizes them into a single records index. After that, everything runs in one process against that local index, offline, until you refresh again to pull fresh data.

This means the tool never redistributes the record datasets (their licenses vary): each user fetches those directly from the source under that source's own terms. The germline is different: IMGT is CC BY 4.0, which permits redistribution with attribution, so it is bundled and germline features work offline out of the box. To pull a newer IMGT germline yourself, run tcr-explorer-refresh --germline. See Data sources.

Requirements

• Python 3.11 or newer.
• Internet access for the initial tcr-explorer-refresh (a few minutes, roughly 60 MB). Offline afterward until you refresh.

Install

pip install tcr-explorer

For authoritative tcrdist similarity scoring (the same metric as tcrdist3, computed offline), install the optional extra:

pip install "tcr-explorer[tcrdist]"

Without it, similarity falls back to the bundled BLOSUM CDR3 distance and says so in a warning. See Similarity scoring.

Or from a checkout:

python -m venv .venv
source .venv/bin/activate          # Windows: .venv\Scripts\activate
pip install -e .

First run

tcr-explorer-refresh

This downloads the four record datasets and builds the index into a local data folder (a platform specific user data directory, or wherever TCR_EXPLORER_DATA points). The IMGT germline is already bundled, so this step does not touch IMGT. Re-run it any time to update the records. If a tool is used before the first refresh, it returns a clear message asking you to run this command.

To pull a fresher IMGT germline than the bundled one, run tcr-explorer-refresh --germline (needs IMGT/GENE-DB reachable). It writes into the local data folder, which the tool prefers over the bundled copy.

Use it

Two front doors, both a single process.

As an MCP server (recommended)

Point your own assistant at TCR Explorer over MCP and ask questions in plain language. This targets desktop and CLI assistants that run a local stdio MCP server. Some web only assistants do not run local stdio MCP servers the same way, so use a desktop or CLI MCP client for the paste and go flow. See Connect your assistant.

As a web app and REST API

PYTHONPATH=src uvicorn tcr_explorer.api:app --port 8000

Open the query box at http://localhost:8000/ui, or call the REST API directly. Health check:

curl http://localhost:8000/health   # {"status":"ok"}

Connect your assistant

TCR Explorer ships an MCP server (console entry point tcr-explorer-mcp). Add this to your assistant's MCP configuration:

{"mcpServers":{"tcr-explorer":{"command":"uvx","args":["--from","tcr-explorer","tcr-explorer-mcp"]}}}

Or paste this prompt into your assistant to have it set the connection up for you:

Set up the TCR Explorer MCP server so you can answer T cell receptor questions against real immunology databases. First install it (pip install tcr-explorer, or use uvx --from tcr-explorer), then run tcr-explorer-refresh once in a terminal to download the datasets into a local folder (a few minutes). Then add an MCP server named tcr-explorer that runs `uvx --from tcr-explorer tcr-explorer-mcp` (if uvx is unavailable, run python -m tcr_explorer.mcp_server). It exposes these read only tools: retrieve_tcr_records, assign_tcr_alleles, get_tcr_dossier, find_similar_tcrs, align_tcr_genes, and ask_tcr. If a tool reports the data is not downloaded yet, tell me to run tcr-explorer-refresh. After adding it, confirm the connection and suggest three example questions I can ask.

You can also run it straight from the public repo without installing: uvx --from git+https://github.com/KilianMaire/tcr-explorer tcr-explorer-mcp.

The read only MCP tools are retrieve_tcr_records, assign_tcr_alleles, get_tcr_dossier, find_similar_tcrs, find_similar_paired_tcrs, align_tcr_genes, and ask_tcr.

REST API

All of these run in process against the local index.

Unified query box

POST /v1/tcr/query routes a single input (a CDR3, a full chain, a gene name, a record id, or a phrase) to the right tool.

curl -s -X POST http://localhost:8000/v1/tcr/query \
  -H "Content-Type: application/json" \
  -d '{"query":"CASSLGGAGGTDTQYF","species":"human"}'

Germline assignment

POST /v1/tcr/assign assigns a TCR sequence (nucleotide or amino acid, CDR3, region, or full chain) to V and J alleles, with per region identity, co optimal ties, CDR3 extraction, and an honest refusal to call a V allele from a bare CDR3.

curl -s -X POST http://localhost:8000/v1/tcr/assign \
  -H "Content-Type: application/json" \
  -d '{"sequence":"CASSLGGAGGTDTQYF","species":"human"}'

Records retrieval

POST /v1/tcr/records searches the harmonized records index.

curl -s -X POST http://localhost:8000/v1/tcr/records \
  -H "Content-Type: application/json" \
  -d '{"cdr3":"CASSLGGAGGTDTQYF","species":"human","limit":20}'

Similarity

POST /v1/tcr/similar finds single chain neighbours (alpha or beta) of a query CDR3. POST /v1/tcr/similar_paired finds alpha/beta paired neighbours of a paired query. See Similarity scoring for the engines.

curl -s -X POST http://localhost:8000/v1/tcr/similar_paired \
  -H "Content-Type: application/json" \
  -d '{"cdr3_a":"CAVNFGGGKLIF","v_a":"TRAV12-1","cdr3_b":"CASSIRSSYEQYF","v_b":"TRBV19","species":"human"}'

Chain reconstruction

POST /reconstruct builds a full membrane bound chain. Provide V, J, and CDR3, or a CDR3 alone (V and J are inferred from the records that carry the same CDR3).

curl -s -X POST http://localhost:8000/reconstruct \
  -H "Content-Type: application/json" \
  -d '{"cdr3_aa":"CASSLGGAGGTDTQYF","species":"human"}'

CDR1 and CDR2 prediction

GET /predict/cdr returns germline CDR1 and CDR2 for a TCR V gene from IMGT germline data.

curl "http://localhost:8000/predict/cdr?v_gene=TRBV12-3&species=human"

Optional: MHC allele sequences

The records index does not contain MHC allele sequences. If you want live lookup of those from EBI IMGT/HLA and IPD-MHC, start the optional hla and mhc proxies with one command:

docker-compose up

The /search endpoint is scoped to these two sources: {"source": "hla"} or {"source": "mhc"}. Any other source returns HTTP 400 pointing at /v1/tcr/records, which is where TCR record search lives.

Environment variables

All optional.

Variable	Default	Description
TCR_EXPLORER_DATA	platform user data dir	Local folder where tcr-explorer-refresh downloads datasets and builds the index
TCR_EXPLORER_MAX_AGE_DAYS	30	Age after which the local index is flagged stale (a refresh is suggested in query warnings, never forced)
RECORDS_INDEX_PATH	<data dir>/records_index.parquet	Override the records index path directly
HLA_SERVER_URL	http://127.0.0.1:8101	HLA allele sequence proxy (optional)
MHC_SERVER_URL	http://127.0.0.1:8105	IPD-MHC allele sequence proxy (optional)
LLM_BASE_URL	(empty)	OpenAI compatible endpoint for the free text ask path (falls back to a heuristic parser when unset)
LLM_MODEL	local-model	Model id for the ask path

Similarity scoring

find_similar_tcrs (and the neighbours block of a dossier) reports which engine scored the result in an engine field.

• tcrdist (when the tcrdist extra is installed). The authoritative tcrdist metric, reproduced offline from the vendored germline CDR table plus the pwseqdist engine (the same engine tcrdist3 uses). It matches tcrdist3 exactly on the integer distances (a parity test against tcrdist3 guards this). Distances are absolute, so you can threshold and compare them across queries. Human and mouse, single chain.
• blosum_cdr3 (the default without the extra). The bundled BLOSUM CDR3 distance, a lighter approximation used only on the CDR3. When this engine runs, the result carries a tcrdist_unavailable warning. It also handles records whose V gene is missing, which tcrdist cannot score.

When tcrdist is active, reference candidates whose V gene is not in the tcrdist table are skipped (their germline loops are unknown) and a tcrdist_candidates_skipped warning reports how many.

Single chain search (find_similar_tcrs, /v1/tcr/similar) works for a query alpha or beta chain. Paired search (find_similar_paired_tcrs, /v1/tcr/similar_paired) scores an alpha/beta query against paired references (reconstructed from the index by pairing key) using the paired tcrdist, which is the sum of the alpha and beta single chain distances. Paired search is tcrdist only: without the extra, or when a query V gene is absent from the reference table, it returns no neighbours with an explanatory warning rather than a misleading fallback.

Data sources

TCR Explorer cites the following. The four record datasets are downloaded on your machine from their official endpoints and are not redistributed; the IMGT germline is bundled with the package under CC BY 4.0. Please cite the ones you use.

• VDJdb (downloaded). Goncharov M. et al. VDJdb in the pandemic era: a compendium of T cell receptors specific for SARS-CoV-2. Nature Methods, 2022. https://github.com/antigenomics/vdjdb-db
• IEDB (downloaded, CC BY 4.0). Vita R. et al. The Immune Epitope Database (IEDB): 2024 update. Nucleic Acids Research, 2025. https://www.iedb.org
• McPAS-TCR (downloaded). Tickotsky N. et al. McPAS-TCR: a manually curated catalogue of pathology associated T cell receptor sequences. Bioinformatics, 2017. https://friedmanlab.weizmann.ac.il/McPAS-TCR/
• TCR3d (downloaded). Lin V. et al. TCR3d 2.0: expanding the T cell receptor structure database. Nucleic Acids Research, 2025. https://tcr3d.ibbr.umd.edu
• IMGT germline (bundled, CC BY 4.0, release 20268-7). Lefranc M-P. et al. IMGT, the international ImMunoGeneTics information system. Reformatted via stitchr and IMGTgeneDL (MIT). See src/tcr_explorer/data/germline/ATTRIBUTION.md. https://www.imgt.org
• tcrdist germline CDR table (bundled, MIT; CDRs from IMGT, CC BY 4.0). Mayer-Blackwell K. et al. TCR meta-clonotypes for biomarker discovery with tcrdist3. eLife, 2021. Used with pwseqdist for offline tcrdist scoring. See src/tcr_explorer/data/tcrdist/ATTRIBUTION.md. https://github.com/kmayerb/tcrdist3

Run tests

PYTHONPATH=src pytest tests/ -v

Architecture

The core is a set of single source pure functions (records retrieval, germline assignment, reconstruction, dossiers, similarity) that read from the locally downloaded index. The REST API, the MCP server, and the web query box all call these same functions in one process.

        MCP server        REST API + /ui query box
             \                    /
              \                  /
        single source pure functions
        (records, assign, reconstruct,
         dossier, similar)
                   |
        local index (built by tcr-explorer-refresh
        from the downloaded records) + bundled IMGT germline

IMGT (IMGT/HLA, IMGT/GENE-DB, IMGT germline, IMGT numbering) is a data source cited throughout. TCR Explorer is an independent tool and is not affiliated with IMGT.