VI

VirtualFlyBrain

org.virtualflybrain/vfb3-mcp

MCP server for Drosophila neuroscience data from VirtualFlyBrain

Yes, your AI can use this right now.Answered a live MCP handshake in 762 ms with no sign-in needed and exposes 11 tools.

Connect it

Settings → Connectors → Add custom connector
URL: https://vfb3-mcp.virtualflybrain.org

11 tools, verified live

Pulled straight from the server with tools/list on 2026-10-17.
get_term_info

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 (

run_query

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 Q

search_terms

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 n

list_search_facets

List the type names search_terms can filter, exclude, boost or demote by, with the number of terms carrying each one. Call this instead of guessing: there are over 200 names, they are the index's own annotations rather than a curated list, and they change as data is added. Use contains to narrow (e.g. contains="lineage" for the ~120 lineage clones, contains="connectivity" to find the connectome fa

resolve_entity

Resolve an unresolved FlyBase-related query string into VFB/FlyBase IDs and metadata. Pass the raw text exactly as the user wrote it (for example "P{VT054895-GAL4.DBD}", "Hb9-GAL4", "SS04495", "MB002B", "PAM cluster", or "dpp"). Do NOT pass resolved IDs such as FBgn/FBal/FBti/FBco/FBst or VFB IDs; if you already have an ID, use the downstream tool directly. Uses tiered resolution: exact name → syn

resolve_combination

Resolve an unresolved split-GAL4 combination name or synonym into its FBco ID and component hemidrivers. Pass the raw combination text exactly as the user wrote it (for example "MB002B" or "SS04495"). Do NOT pass an FBco ID; if you already have one, use the downstream tool directly. Uses tiered resolution: exact name → synonym → broad pattern match. Returns FBco ID, combination name, matched synon

list_connectome_datasets

List available connectome datasets with their labels and symbols. Use the returned symbols when constructing exclude_dbs arguments for query_connectivity. Common datasets include Hemibrain (hb), FAFB (fafb), MANC, and others. Call this tool if unsure which dataset symbols are valid.

query_connectivity

Query synaptic connectivity between Drosophila neuron classes across ALL connectome datasets simultaneously for comparative connectomics. This is NOT pre-cached — it runs live queries, so expect slow responses (up to several minutes). Set both upstream_type AND downstream_type to filter connections between two specific neuron classes (e.g., "What Tm1→T3 connections exist across all datasets?"). At

get_predicted_neurotransmitters

Get the PREDICTED neurotransmitter(s) for a Drosophila neuron class — itself or any subclass — from per-instance connectome predictions (each reconstructed neuron carries a predicted transmitter with a confidence). Use this for "what neurotransmitter does <cell type> use?" when you want the data-driven prediction and its confidence. By default results are aggregated to flat per-class rows (one per

get_known_neurotransmitters

Get the KNOWN (curated) neurotransmitter(s) for a Drosophila neuron class and its subclasses, from the ontology's classification rather than per-instance predictions — so there is no confidence. Use this for "what neurotransmitter is <cell type> known to use?" when you want the curated/established answer. Returns one row per (cell type, neurotransmitter): {cell_type_id, cell_type, nt_id, nt_label}

get_hierarchy

Build a hierarchy tree for a VFB term, showing ancestors (parents) and/or descendants (children). Use relationship "part_of" for brain region structure (e.g. "what are the parts of the mushroom body?") and "subclass_of" for cell type hierarchies (e.g. "what types of Kenyon cell are there?"). Descendants are returned as a nested tree for both relationship types. Ancestors are returned as a nested c

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