In-depth architectural comparison of the ClickHouse and MCP Server Couchbase 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
ClickHouse
Databases · Local stdio
Quality: 53/100 (Good) | Auth: other
MCP Server Couchbase
Databases · Local stdio
Quality: 63/100 (Good) | Auth: other
Verdict Summary: Choose ClickHouse if you need specialized Databases tools running via a local process. Choose MCP Server Couchbase 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?
Choose ClickHouse when:
You need dedicated capabilities in the Databases domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: other (Free / Open Source).
You have access to required keys: MCP_CLICKHOUSE_DSN.
Read-only MCP server for ClickHouse metadata, parameterized queries, and plan analysis.
Couchbase MCP server provides unfied access to both Capella cloud and self-managed clusters for document operations, SQL++ queries and natural language data analysis.
List configured connection profiles. Call first when picking a non-default profile.
run_query
Execute read-only `SELECT` (CTEs allowed), one statement per call. Returns rows inline as CSV, or a `chx://snapshots/{id}` URI when `snapshot=true`. Inline limit: 500 rows (hard ceiling 1 000). Snapshot limit: 10 000 rows (hard ceiling 50 000).
run_show
Execute one `SHOW` statement — chiefly `SHOW CREATE TABLE`/`VIEW`/`DICTIONARY` for DDL a listing cannot give you: codecs, TTLs, the full column list. No `INTO OUTFILE`.
analyze_query
EXPLAIN` a read-only `SELECT`; returns plan, pipeline or syntax, no result rows.
MCP Server Couchbase Tools (21)
get_buckets_in_cluster
Ready-to-Paste Client Configurations
Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).
ClickHouse is categorized under Databases and uses a local stdio subprocess. In contrast, MCP Server Couchbase belongs to Databases using local stdio subprocess. Select ClickHouse when you need capabilities focused on databases and MCP Server Couchbase when you require tools for databases.
Get the names of all the accessible buckets in the cluster.
get_server_configuration_status
Get the server status and configuration without establishing connection.
This tool can be used to verify if the server is running and check the configuration.
test_cluster_connection
Test the connection to Couchbase cluster and optionally to a bucket.
This tool verifies the connection to the Couchbase cluster and bucket by establishing the connection if it is not already established.
If bucket name is not provided, it will not try to connect to the bucket specified in the MCP server settings.
Returns connection status and basic cluster information.
get_scopes_and_collections_in_bucket
Get the names of all scopes and collections in the bucket.
Returns a dictionary with scope names as keys and lists of collection names as values.
get_collections_in_scope
Get the names of all collections in the given scope and bucket.
get_scopes_in_bucket
Get the names of all scopes in the given bucket.
get_cluster_health_and_services
Get cluster health status and list of all running services.
This tool provides health monitoring by:
- Getting health status of all running services with latency information (via ping)
- Listing all services running on the cluster with their endpoints
- Showing connection status and node information for each service
If bucket_name is provided, it actively pings services from the perspective of the bucket.
Otherwise, it uses cluster-level ping to get the health status of the cluster.
Returns:
- Cluster health status with service-level connection details and latency measurements
get_document_by_id
Get a document by its ID from the specified scope and collection.
If the document is not found, it will raise an exception.
lookup_subdocument
Look up parts of a document without fetching the whole thing, using Couchbase
sub-document operations. Use this instead of get_document_by_id when you only need
a few fields, a presence check, or the size of an array/object inside a document —
AND you already know the exact field path(s) to look up (e.g. from a prior
get_document_by_id call on this same document, from the user explicitly naming the
field, or from a known/confirmed schema for this collection).
IMPORTANT: Do NOT guess field paths. If you don't already know the document's exact
field names/structure, call get_document_by_id first (or instead) — a guessed path
that doesn't exist returns a per-path error here rather than the real data, and
reporting "not found" for a wrong guess is worse than just fetching the whole
document and reading the right field.
Provide one or more of the following. Each is a list of sub-document paths using
Couchbase's dot/bracket path syntax (e.g. "address.city", "tags[0]", "tags[-1]" for
the last array element):
- get_paths: fetch the VALUE at each path.
- exists_paths: check whether each path exists, without fetching its value (cheaper
than get_paths — no payload transfer — when you only need a yes/no answer).
- count_paths: get the number of elements in the array or object at each path (fails
per-path if the path isn't an array/object).
At least one of get_paths, exists_paths, or count_paths must be provided. As a rule of
thumb, keep the combined number of paths across all three to 16 or fewer — Couchbase
limits subdocument operations per call, though the exact limit is server-side and may
change. If the server rejects the call (too many paths, or another constraint like path
length or nesting depth), the whole call fails with {"error": "..."}.
A path that doesn't exist (or otherwise fails, e.g. count on a non-array/object) does
NOT fail the whole call — it is reported individually as {"error": ...} in the
returned dict so the other requested paths can still be resolved.
Returns a dict with a key for each category that was requested (only requested
categories are included):
{
"get": {"<path>": {"value": <value>} | {"error": "..."}},
"exists": {"<path>": {"value": true | false} | {"error": "..."}},
"count": {"<path>": {"value": <count>} | {"error": "..."}},
}
On a connection/lookup failure, or an invalid request (no paths / too many paths),
returns {"error": "<message>"} instead.
get_schema_for_collection
Get the schema for a collection in the specified scope.
Returns a dictionary with the collection name and the schema returned by running INFER query on the Couchbase collection.
run_sql_plus_plus_query
Run a SQL++ query on a scope and return the results as a list of JSON objects.
The query will be run on the specified scope in the specified bucket.
The query should use collection names directly without bucket/scope prefixes, as the scope context is automatically set.
Use ``named_parameters`` to bind values to ``$name`` placeholders in the
query instead of concatenating user input into the statement. This prevents
SQL++ injection
Example:
query = "SELECT * FROM users WHERE age > 18"
# Incorrect: "SELECT * FROM bucket.scope.users WHERE age > 18"
For creating a new index, prefer the create_index tool over a raw CREATE INDEX statement
here — it defers the build by default and tells you the recommended next step. Use
list_indexes to check whether an index is online before relying on it in a query plan.
explain_sql_plus_plus_query
Generate and evaluate an EXPLAIN plan for a SQL++ query. It provides information about the execution plan for the query.
The EXPLAIN statement is run in the specified scope in the specified bucket.
It returns query metadata along with an extracted plan and plan evaluation.