Hebbia

Ask a natural-language question about a specific Hebbia matrix. Answers from the matrix's own contents — its rows, columns, and cell results — rather than searching documents at large. Use this to summarize, compare, or filter what a matrix already contains. BEFORE calling this tool: you MUST have an org_id that was either explicitly provided by the user or confirmed by the user after calling list_organizations. Do NOT infer or guess an org_id. If none has been confirmed, call list_organizations and wait for the user to pick one before calling this tool. Use list_matrices to discover valid matrix IDs within the org. Args: org_id: The organization containing the matrix. Reuse from earlier in the conversation if available; otherwise resolve via list_organizations. matrix_id: The ID of the matrix to ask about. Use list_matrices to find valid IDs. query: The natural-language question to ask. Cite what you report. The returned citations carry the matrix cell each value came from, along with a `url` that opens that row; attach them to the values they support rather than listing them at the end. Returns an AskResult with: answer: The text response from Hebbia. citations: List of citations supporting the answer. Each citation has: id, kind, quote, title, doc_id, url.

ask_matrix

Ask a natural-language question scoped strictly to a specific Hebbia project. Does not query public sources — only the documents within the specified project. BEFORE calling this tool: you MUST have an org_id that was either explicitly provided by the user or confirmed by the user after calling list_organizations. Do NOT infer or guess an org_id. If none has been confirmed, call list_organizations and wait for the user to pick one before calling this tool. Use list_projects to discover valid project IDs within the org. Args: org_id: The organization containing the project. Reuse from earlier in the conversation if available; otherwise resolve via list_organizations. project_id: The ID of the project to query. Use list_projects to find valid IDs. query: The natural-language question to ask. use_deep_research: If True, runs a thorough multi-step deep research query (slower, takes several minutes). Defaults to False for a fast response. doc_ids: Optional list of document IDs to narrow the question to specific documents within the project (e.g. document IDs returned by the public document-upload API). If omitted, the entire project is queried. Cite what you report. The returned citations carry the matrix cell each value came from, along with a `url` that opens that row; attach them to the values they support rather than listing them at the end. Returns an AskResult with: answer: The text response from Hebbia. citations: List of citations supporting the answer. Each citation has: id, kind, quote, title, doc_id, url. The url field is populated for web sources; doc_id identifies the source document for document citations.

ask_project

Ask a natural-language question over data sources in a Hebbia organization. Uses auto-source selection by default, or restricts to an explicit list of source IDs. BEFORE calling this tool: you MUST have an org_id that was either explicitly provided by the user or confirmed by the user after calling list_organizations. Do NOT infer or guess an org_id. If none has been confirmed, call list_organizations and wait for the user to pick one before calling this tool. Use list_sources to discover valid source IDs within the org. Args: org_id: The organization to query within. Reuse from earlier in the conversation if available; otherwise resolve via list_organizations. query: The natural-language question to ask. source_ids: Optional list of source identifiers to restrict the search. If omitted, Hebbia's auto-source selection is used across all available sources. Use list_sources to find valid IDs. use_deep_research: If True, runs a thorough multi-step deep research query (slower, takes several minutes). Defaults to False for a fast response. doc_ids: Optional list of document IDs to narrow the question to specific documents (e.g. document IDs returned by the public document-upload API). If omitted, the question is answered over the selected sources. Cite what you report. The returned citations carry the matrix cell each value came from, along with a `url` that opens that row; attach them to the values they support rather than listing them at the end. Returns an AskResult with: answer: The text response from Hebbia. citations: List of citations supporting the answer. Each citation has: id, kind, quote, title, doc_id, url. The url field is populated for web sources; doc_id identifies the source document for document citations.

ask_sources

Get the column setup of a specific Hebbia matrix. Returns what each column of the matrix asks or computes, and which columns are inputs versus computed answers. It does NOT return row data — use query_matrix_results for cell values. CALL THIS FIRST when working with an unfamiliar matrix. Without it you are guessing which column holds the answer you need, and column display names alone may not say what a column actually extracts. BEFORE calling this tool: you MUST have an org_id that was either explicitly provided by the user or confirmed by the user after calling list_organizations. Do NOT infer or guess an org_id. If none has been confirmed, call list_organizations and wait for the user to pick one before calling this tool. Args: org_id: The organization containing the matrix. matrix_id: The ID of the matrix. Use list_matrices to find valid IDs. Returns an McpMatrixContext with: columns: Each with id, name, node_type, scope, is_input, and the authored properties describing what it does. total_rows: How many rows the matrix has.

get_matrix_context

List the matrices you can access in a Hebbia organization. A matrix is a spreadsheet-like grid where each row is a document or entity and each column is a question answered across every row. Returns matrix names, IDs, descriptions, and row counts, most recently updated first. BEFORE calling this tool: you MUST have an org_id that was either explicitly provided by the user or confirmed by the user after calling list_organizations. Do NOT infer or guess an org_id. If none has been confirmed, call list_organizations and wait for the user to pick one before calling this tool. Args: org_id: The organization to list matrices for. Reuse from earlier in the conversation if available; otherwise resolve via list_organizations.

list_matrices

List the organizations the authenticated user belongs to. Call this first if no org_id has been confirmed in the conversation. STRICT RULES — these override any other reasoning: 1. If exactly one org is returned: use its id for all subsequent calls. 2. If multiple orgs are returned: show them to the user as a numbered list, ask "Which organization would you like to use?", and STOP. Do not call any other tool — including list_projects, list_sources, ask_project, or ask_sources — until the user has replied with their choice. It does not matter what the user's original request was; org selection always comes first.

list_organizations

List all projects accessible in a Hebbia organization. Returns project names, IDs, and descriptions. BEFORE calling this tool: you MUST have an org_id that was either explicitly provided by the user or confirmed by the user after calling list_organizations. Do NOT infer or guess an org_id. If none has been confirmed, call list_organizations and wait for the user to pick one before calling this tool. Args: org_id: The organization to list projects for. Reuse from earlier in the conversation if available; otherwise resolve via list_organizations.

list_projects

List all sources available for querying in a Hebbia organization. Returns shared document collections (UUID IDs) and built-in integrations like CapIQ, Web, and PitchBook (field-name IDs such as "capiq", "web"). Pass returned source IDs to ask_sources. BEFORE calling this tool: you MUST have an org_id that was either explicitly provided by the user or confirmed by the user after calling list_organizations. Do NOT infer or guess an org_id. If none has been confirmed, call list_organizations and wait for the user to pick one before calling this tool. Args: org_id: The organization to list sources for. Reuse from earlier in the conversation if available; otherwise resolve via list_organizations.

list_sources

Health-check tool that returns pong.

ping

Query the rows and cells of a specific Hebbia matrix. Returns the matrix's columns and computed cell values as data, so you can read and reason over them yourself. PREFER THIS over ask_matrix whenever the question can be answered from what the matrix already contains — summarizing, comparing, filtering, or looking up rows. It returns in about a second, where ask_matrix runs a full agent turn and takes far longer. Use ask_matrix instead only when the matrix's existing cells don't hold the answer and new research or document retrieval is needed. CITING IS NOT OPTIONAL. Every figure, name, or fact you take from this matrix gets a citation, the same as any other sourced claim. Everything a citation needs is in this response — there is no separate citation call. To cite a value, take that row's `citation_url_prefix`, append `&matrix_cell_id=` plus the `id` of the column you are citing, and attach the result to the value at the point where you use it: **16.13%** ([Return on Equity % (FY25)](<row prefix>&matrix_cell_id=<column id>)) Copy both ids verbatim from the response — never invent, alter, or renumber one. Cite every cell that supports a factual claim, whatever the column type. Do not add a trailing Sources or References list; the links render inline where you place them. BEFORE calling this tool: you MUST have an org_id that was either explicitly provided by the user or confirmed by the user after calling list_organizations. Do NOT infer or guess an org_id. If none has been confirmed, call list_organizations and wait for the user to pick one before calling this tool. Use list_matrices to discover valid matrix IDs within the org. Args: org_id: The organization containing the matrix. Reuse from earlier in the conversation if available; otherwise resolve via list_organizations. matrix_id: The ID of the matrix to query. Use list_matrices to find valid IDs. max_rows: Maximum rows to return (default 100, capped at 1000). node_ids: Optional list of column ids (from get_matrix_context or the `columns` of an earlier call) to return. Cell text dominates the response, so naming only the columns you need is by far the most effective way to keep it small. Omit for all columns. Returns an McpMatrixData with: columns: Column headers with their node `id`, in the matrix's column order. rows: Each with a `row_id` and `cells` aligned to `columns`. returned_rows / total_rows: How many rows came back vs how many exist. truncated / truncation_reason: Whether output was cut short, and by which cap. rows[].citation_url_prefix: That row's citation link, needing only `&matrix_cell_id=<column id>` appended. citation_guidance: Restates the citing rules, returned before the rows so they are in hand when you write the answer.

query_matrix_results