Virtual Fly Brain

Get term info for a VFB or anatomy ontology entity (VFB_*, FBbt_*, etc.). THIS IS THE QUERY DISCOVERY TOOL: the response's "Queries" array lists the valid query_type values that run_query accepts for this entity. ALWAYS call get_term_info before run_query unless you already obtained the query_type from a previous get_term_info call in this conversation. Returns: SuperTypes (classification), Tags (data flags like has_image, has_neuron_connectivity), Queries (valid query_types for run_query), RelatedTools (other MCP tools applicable to this entity, with default_args ready to copy — e.g. get_hierarchy with subclass_of for cell types or part_of for nervous-system regions), Images (keyed by template brain ID), Publications, Synonyms. Supports batch — pass an array of IDs to fetch in parallel; batch results are returned as a JSON object keyed by ID. To build VFB browser URLs from the Images field: https://v2.virtualflybrain.org/org.geppetto.frontend/geppetto?id=<VFB_ID>&i=<TEMPLATE_ID>,<IMAGE_ID1>,<IMAGE_ID2> — id= sets the focus term and i= lists images for the 3D viewer (template ID must be first in i= to set the coordinate space).

Run a pre-computed query on a VFB entity. REQUIRED WORKFLOW: (1) call get_term_info on the ID first; (2) read the response's "Queries" array; (3) pass one of those values as query_type. Calling run_query with a guessed query_type will return an error. If a query returns empty rows or an error, the entity does not support that query_type or has no data for it — try a different query_type from the Queries array, or try a related entity (e.g. its parent class via get_hierarchy). Empty results do NOT mean the answer is unknown — only that this call did not return it. NEVER fabricate results from training data when a query is empty; tell the user clearly what was tried. NEVER pass tool names like "get_term_info" or "search_terms" as query_type — those are separate tools. Common query_types by entity kind: PaintedDomains, AllAlignedImages, AlignedDatasets, AllDatasets (templates); SimilarMorphologyTo, NeuronInputsTo, NeuronNeuronConnectivityQuery, NeuronRegionConnectivityQuery (individual neurons); ListAllAvailableImages, SubclassesOf, PartsOf, NeuronsPartHere, NeuronsSynaptic, ExpressionOverlapsHere, DownstreamClassConnectivity, UpstreamClassConnectivity (classes). Supports batch — pass an array of IDs (same query_type) or a "queries" array of {id, query_type} pairs; batch results are keyed by "ID::query_type". Results are PAGED: the first 25 rows by default (change with limit/offset) plus the true total as "count". ALWAYS read "count_status" before quoting "count": "exact" means count is the true total; "unavailable" means the query FAILED upstream and count is -1, which is NOT zero and must never be reported as "no results" — read "_note" and tell the user the query could not be run. Image/thumbnail columns are excluded by default to save space - pass include_images=true to include them. FlyBase integration is via query_types too: FindStocks (fly stocks for a FlyBase feature ID - FBgn/FBal/FBti/FBtp/FBco/FBst) and FindComboPublications (publications for an FBco split-GAL4 combination). Get those IDs from resolve_entity / resolve_combination first, then run_query with the ID and the query_type. Include FlyBase links in output: https://flybase.org/reports/{ID}.

Search VFB terms. This is the search virtualflybrain.org itself runs — the same Solr query, the same ranking — so what comes back first here is what a user would see first on the site. USE filter_types BY DEFAULT. Unfiltered searches mix scRNAseq artifacts and developmental stages in with the entity the user wants. Common filter_types recipes: - Neuron classes: ["neuron", "class"] - Individual neurons with images: ["neuron", "has_image"] - Neurons with connectome data: ["neuron", "has_neuron_connectivity"] - Brain regions / neuropils: ["anatomy"] - Genes: ["gene"] - Driver lines / expression patterns: ["expression_pattern"] - Datasets: ["dataset"] There are over 200 type names and they change as data is added, so do NOT guess them: call list_search_facets to see the current vocabulary (optionally filtered, e.g. contains="lineage"). Names are matched case- and separator-insensitively, and a name that does not exist is an error with suggestions rather than a silently empty result. Deprecated terms are excluded by the search itself — you do not need exclude_types: ["deprecated"], and adding it is harmless but pointless. Stage filtering: VFB covers adult, larval, and embryonic data, and many anatomical FBbt classes are stage-agnostic. Do NOT add "adult" or "larva" to filter_types by default — only add them when the user is explicit about a stage (e.g. "adult Kenyon cells", "larval mushroom body"). Default searches should leave stage out so stage-agnostic classes and all life stages are visible. Useful flags: - unique=true (the default) → one row per term. Turn it OFF only when you need to see WHICH synonym matched; with unique=false a term appears once per matching synonym, so "Kenyon cell" can return the same ID several times. - minimize_results=true → top 10, essential fields only, for exploratory searches. - auto_fetch_term_info=true → if an exact label match is found, returns get_term_info in the same response. - boost_types=["has_image", "has_neuron_connectivity"] → float data-rich entities to the top of the list without excluding anything else. - demote_types=["expression_pattern_fragment"] → sink noisy types to the bottom of the list instead of removing them. If the search returns no good matches, do NOT fall back to training-data answers — try alternative spellings, synonyms, broader terms, or different filter_types. Multiple filter_types are ANDed (results must match ALL). Multiple exclude_types are ORed (any match excludes). boost_types and demote_types re-order without excluding; boost wins if a term matches both.