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Documentation Index

Fetch the complete documentation index at: https://docs.cognee.ai/llms.txt

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Cognee MCP currently exposes 14 tools for memory management, retrieval, and dataset operations. Unless noted otherwise, parameter names and defaults below reflect the current MCP server implementation.
Some MCP parameters use compact transport-friendly encodings:
  • datasets and session_ids are comma-separated strings, not JSON arrays.
  • top_k must be between 1 and 100.
  • cognify.data accepts either a single string or a JSON array of strings for batch ingestion.

Available Tools

Still available for lower-level control or existing integrations.
Transform ingested data into a structured knowledge graph.
ParameterTypeDefaultNotes
datastrrequiredA single string or a JSON array of strings for batch ingestion.
dataset_namestrmain_datasetDataset to populate.
graph_model_filestrNonePath to a custom graph model file.
graph_model_namestrNoneClass name inside graph_model_file.
custom_promptstrNoneCustom extraction prompt.
If graph_model_file is set, graph_model_name should also be provided.
Reset the local MCP-managed store for a fresh start.This tool has no parameters.
prune is not available in API mode.
Use these after retrieval when you need a fuller document view or nearby chunk context.
Retrieve a source document and its chunks.
ParameterTypeDefaultNotes
document_idstrrequiredDocument ID. A chunk ID is also accepted and resolves to its parent document.
include_metadataboolTrueInclude metadata in the response.
max_chunksint0Use 0 to return all chunks.
Retrieve nearby chunks from the same document.
ParameterTypeDefaultNotes
chunk_idstrrequiredTarget chunk ID.
neighbor_countint2Number of chunks to fetch on each side.
include_targetboolTrueInclude the original chunk in the response.
directionstrbothOne of both, forward, or backward.
get_document and get_chunk_neighbors are not available in API mode.
Store a user-assistant exchange so Cognee can process it into memory and related rules.
ParameterTypeDefaultNotes
datastrrequiredInteraction content to ingest.
List datasets and their data items with IDs for deletion operations.
ParameterTypeDefaultNotes
dataset_idstrNoneOptional dataset UUID. When omitted, lists all datasets.
Remove a specific data item from a dataset.
ParameterTypeDefaultNotes
data_idstrrequiredData item UUID.
dataset_idstrrequiredDataset UUID containing the item.
modestrsoftEither soft or hard.
Delete an entire dataset by name.
ParameterTypeDefaultNotes
dataset_namestrrequiredDataset name to delete.
Check current and recent pipeline runs for a dataset.
ParameterTypeDefaultNotes
dataset_namestrmain_datasetDataset to inspect.
pipelineslist[str]["cognify_pipeline"]Optional list of pipeline names to restrict the status view.
delete_dataset and cognify_status are not available in API mode. list_data(dataset_id=...) also requires direct mode for detailed per-item listing.

Usage Notes

  • For new integrations, start with remember to store data and recall to retrieve it.
  • Use improve when you want to enrich an existing graph or bridge session memory into permanent memory.
  • Use forget to remove a dataset or wipe all memory owned by the current user.
  • Reach for cognify, search, and prune only when you need lower-level control or are maintaining an older workflow.
  • Use get_document or get_chunk_neighbors after a CHUNKS result when the initial match is too narrow.
  • Use cognify_status to verify indexing before querying a freshly processed dataset.

Next Steps

Client Integrations

Learn how to use these tools with your AI development environment