In-depth architectural comparison of the Kirbah Mcp Youtube and Chroma Mcp MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.
At a Glance & Executive Verdict
Kirbah Mcp Youtube
Databases · Local stdio
Quality: 56/100 (Good) | Auth: No auth required
Chroma Mcp
Databases · Local stdio
Quality: 63/100 (Good) | Auth: API Key required
Verdict Summary: Choose Kirbah Mcp Youtube if you need specialized Databases tools running via a local process. Choose Chroma Mcp if your workspace requires Databases integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.
Which MCP Server Should You Choose?
K
Choose Kirbah Mcp Youtube when:
You need dedicated capabilities in the Databases domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
Kirbah Mcp Youtube is categorized under Databases and uses a local stdio subprocess. In contrast, Chroma Mcp belongs to Databases using local stdio subprocess. Select Kirbah Mcp Youtube when you need capabilities focused on databases and Chroma Mcp when you require tools for databases.
Retrieves a list of trending videos for a given region and optional category, with **lean** details and engagement ratios.
getVideoCategories
Retrieves available YouTube video categories (ID and title) for a specific region, providing **essential data only**.
getVideoComments
Retrieves comments for a YouTube video. Allows sorting, limiting results, and fetching a small number of replies per comment.
findConsistentOutlierChannels
Identifies channels that consistently perform as outliers within a specific niche. **Requires a MongoDB connection.
Chroma Mcp Tools (13)
chroma_list_collections
List all collection names in the Chroma database with pagination support.
Args:
limit: Optional maximum number of collections to return
offset: Optional number of collections to skip before returning results
Returns:
List of collection names or ["__NO_COLLECTIONS_FOUND__"] if database is empty
chroma_create_collection
Create a new Chroma collection with configurable HNSW parameters.
Args:
collection_name: Name of the collection to create
embedding_function_name: Name of the embedding function to use. Options: 'default', 'cohere', 'openai', 'jina', 'voyageai', 'ollama', 'roboflow'
metadata: Optional metadata dict to add to the collection
chroma_peek_collection
Peek at documents in a Chroma collection.
Args:
collection_name: Name of the collection to peek into
limit: Number of documents to peek at
chroma_get_collection_info
Get information about a Chroma collection.
Args:
collection_name: Name of the collection to get info about
chroma_get_collection_count
Get the number of documents in a Chroma collection.
Args:
collection_name: Name of the collection to count
chroma_modify_collection
Modify a Chroma collection's name or metadata.
Args:
collection_name: Name of the collection to modify
new_name: Optional new name for the collection
new_metadata: Optional new metadata for the collection
chroma_fork_collection
Fork a Chroma collection.
Args:
collection_name: Name of the collection to fork
new_collection_name: Name of the new collection to create
metadata: Optional metadata dict to add to the new collection
chroma_delete_collection
Delete a Chroma collection.
Args:
collection_name: Name of the collection to delete
chroma_add_documents
Add documents to a Chroma collection.
Args:
collection_name: Name of the collection to add documents to
documents: List of text documents to add
ids: List of IDs for the documents (required)
metadatas: Optional list of metadata dictionaries for each document
chroma_query_documents
Query documents from a Chroma collection with advanced filtering.
Args:
collection_name: Name of the collection to query
query_texts: List of query texts to search for
n_results: Number of results to return per query
where: Optional metadata filters using Chroma's query operators
Examples:
- Simple equality: {"metadata_field": "value"}
- Comparison: {"metadata_field": {"$gt": 5}}
- Logical AND: {"$and": [{"field1": {"$eq": "value1"}}, {"field2": {"$gt": 5}}]}
- Logical OR: {"$or": [{"field1": {"$eq": "value1"}}, {"field1": {"$eq": "value2"}}]}
where_document: Optional document content filters
Examples:
- Contains: {"$contains": "value"}
- Not contains: {"$not_contains": "value"}
- Regex: {"$regex": "[a-z]+"}
- Not regex: {"$not_regex": "[a-z]+"}
- Logical AND: {"$and": [{"$contains": "value1"}, {"$not_regex": "[a-z]+"}]}
- Logical OR: {"$or": [{"$regex": "[a-z]+"}, {"$not_contains": "value2"}]}
include: List of what to include in response. By default, this will include documents, metadatas, and distances.
chroma_get_documents
Get documents from a Chroma collection with optional filtering.
Args:
collection_name: Name of the collection to get documents from
ids: Optional list of document IDs to retrieve
where: Optional metadata filters using Chroma's query operators
Examples:
- Simple equality: {"metadata_field": "value"}
- Comparison: {"metadata_field": {"$gt": 5}}
- Logical AND: {"$and": [{"field1": {"$eq": "value1"}}, {"field2": {"$gt": 5}}]}
- Logical OR: {"$or": [{"field1": {"$eq": "value1"}}, {"field1": {"$eq": "value2"}}]}
where_document: Optional document content filters
Examples:
- Contains: {"$contains": "value"}
- Not contains: {"$not_contains": "value"}
- Regex: {"$regex": "[a-z]+"}
- Not regex: {"$not_regex": "[a-z]+"}
- Logical AND: {"$and": [{"$contains": "value1"}, {"$not_regex": "[a-z]+"}]}
- Logical OR: {"$or": [{"$regex": "[a-z]+"}, {"$not_contains": "value2"}]}
include: List of what to include in response. By default, this will include documents, and metadatas.
limit: Optional maximum number of documents to return
offset: Optional number of documents to skip before returning results
Returns:
Dictionary containing the matching documents, their IDs, and requested includes
chroma_update_documents
Update documents in a Chroma collection.
Args:
collection_name: Name of the collection to update documents in
ids: List of document IDs to update (required)
embeddings: Optional list of new embeddings for the documents.
Must match length of ids if provided.
metadatas: Optional list of new metadata dictionaries for the documents.
Must match length of ids if provided.
documents: Optional list of new text documents.
Must match length of ids if provided.
Returns:
A confirmation message indicating the number of documents updated.
Raises:
ValueError: If 'ids' is empty or if none of 'embeddings', 'metadatas',
or 'documents' are provided, or if the length of provided
update lists does not match the length of 'ids'.
Exception: If the collection does not exist or if the update operation fails.