mcp-clickhousex
A read-only-by-default MCP server for ClickHouse that exposes schema discovery, read-only queries, SHOW/EXPLAIN analysis, optional snapshots, and opt-in write commands across multiple connection profiles.
List profiles (
list_profiles) and inspect cluster properties/limits (get_cluster_properties)Run read-only SQL (
run_query) supporting SELECT/WITH, parameters, row caps, inline CSV or persisted snapshot results (7-day expiry)Execute SHOW statements (
run_show) for introspection like databases, tables, CREATE statementsAnalyze queries (
analyze_query) with EXPLAIN plan, pipeline, and syntax outputDiscover schema via
list_databases,list_tables,list_columns, plus manualrun_queryoversystem.*tablesOptional writes (
run_command) only when a profile enablesALLOW_WRITE; per-profile refusal otherwiseMulti-server support via named profiles configured through config.json or environment variables
Enforced safety:
readonly=1on read clients, row/time limits, no external table functions or query-level SETTINGS for read tools
Provides tools for executing read-only SELECT and SHOW queries, analyzing query plans, and discovering metadata (databases, tables, columns) on ClickHouse instances.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-clickhousexexecute query: SELECT name FROM system.tables LIMIT 5"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP ClickHouse Tool
A read-only-by-default Model Context Protocol (MCP) server for ClickHouse that provides schema discovery, read-only queries, execution-plan analysis, opt-in writes, and profile-based access to multiple servers from a single toolset deployment.
Read-only is enforced by the engine, not by SQL text matching: the query tools' clients carry ClickHouse's readonly=1, so writes, external table functions and query-level SETTINGS are refused by the server being queried. Writes live behind a separate tool that is not registered at all until a profile asks for it.
Requirements: Python 3.13+, a running ClickHouse instance, and connection details via environment variables or a config file.
Quick start
Set a DSN and run the server with MCP Inspector:
# Option 1: Run directly with uvx (no clone needed)
export MCP_CLICKHOUSE_DSN="http://default:@localhost:8123/default"
npx -y @modelcontextprotocol/inspector@latest uvx mcp-clickhousex# Option 2: Run from source (clone repo, then)
export MCP_CLICKHOUSE_DSN="http://default:@localhost:8123/default"
npx -y @modelcontextprotocol/inspector@latest uv run mcp-clickhousexRelated MCP server: io.github.Aguantar/clickhouse-dataops-mcp
Configuration
A profile is one ClickHouse connection: a DSN plus the row and timeout caps that apply to it. A profile named default always exists; every tool takes an optional profile to reach another, and list_profiles reports what is configured.
Settings come from three sources, merged field by field, later winning:
the user-scoped
config.json— any number of profiles;MCP_CLICKHOUSE_PROFILES_<NAME>_<FIELD>environment variables — any number of profiles;flat
MCP_CLICKHOUSE_<FIELD>environment variables — thedefaultprofile only.
Because the merge is per field rather than per profile, a config.json can carry the full set while a flat MCP_CLICKHOUSE_DSN repoints the default profile at a local server, leaving its other fields intact. With none of the three present, default falls back to http://default:@localhost:8123/default.
Each setting has one field name, spelled three ways — MCP_CLICKHOUSE_<FIELD>, MCP_CLICKHOUSE_PROFILES_<NAME>_<FIELD>, or the field lowercased as a JSON key:
Field | Default | Hard ceiling |
|
| — |
| none | — |
| 500 | 1 000 |
| 30 | 300 |
| 10 000 | 50 000 |
| 120 | 300 |
|
| — |
| 60 | 600 |
Caps are per profile. A value above its ceiling is clamped at startup; a value that is not an integer falls back to the default, and a value that is not a boolean leaves ALLOW_WRITE off.
Single connection: flat environment variables are the shortest path.
# Connection DSN.
export MCP_CLICKHOUSE_DSN="http://user:password@host:8123/database"
# Optional description for the default profile (tooling/AI discovery).
export MCP_CLICKHOUSE_DESCRIPTION="Primary cluster"
# Optional caps, defaults shown.
export MCP_CLICKHOUSE_QUERY_MAX_ROWS="500"
export MCP_CLICKHOUSE_QUERY_COMMAND_TIMEOUT_SECONDS="30"
export MCP_CLICKHOUSE_SNAPSHOT_MAX_ROWS="10000"
export MCP_CLICKHOUSE_SNAPSHOT_COMMAND_TIMEOUT_SECONDS="120"
# Optional write access, off by default; also controls whether run_command
# is advertised at all.
export MCP_CLICKHOUSE_ALLOW_WRITE="false"
export MCP_CLICKHOUSE_WRITE_COMMAND_TIMEOUT_SECONDS="60"Multiple connections: use the user-scoped config.json, which keeps credentials out of the host's process environment.
Unix-like:
~/.config/mcp-clickhousex/config.jsonWindows:
%USERPROFILE%\.config\mcp-clickhousex\config.json
{
"profiles": {
"default": {
"dsn": "http://default:@localhost:8123/default",
"description": "Primary",
"query_max_rows": 500,
"query_command_timeout_seconds": 60,
"snapshot_max_rows": 10000,
"snapshot_command_timeout_seconds": 120
},
"warehouse": {
"dsn": "http://user:pass@warehouse:8123/analytics",
"description": "Warehouse"
},
"writer": {
"dsn": "http://etl:pass@warehouse:8123/analytics",
"description": "Warehouse, write-enabled",
"allow_write": true,
"write_command_timeout_seconds": 120
}
}
}Nothing stops one profile from both reading and writing, but a separate write-enabled profile is the shape worth copying: it gives the writes their own DSN, so the credentials behind them can be scoped to what they actually need while the read profiles stay on a login whose grants stop at SELECT.
Profile names are case-insensitive and must be alphanumeric — no underscores or hyphens, since the structured env form splits on _ (MCP_CLICKHOUSE_PROFILES_WAREHOUSE_DSN is profile warehouse, field DSN). A name that breaks the rule is skipped, as is a config.json that is missing, unreadable, or not shaped {"profiles": {…}}; the server starts on whatever sources remain rather than failing.
DSN syntax: scheme://user:password@host:port/database. An https:// or clickhouses:// scheme enables TLS, and query-string parameters reach the driver (?connect_timeout=10) — except readonly, which the server always applies last, from the profile's ALLOW_WRITE.
URL-reserved characters in the username or password must be percent-encoded — # → %23, ? → %3F, / → %2F, @ → %40, % → %25. Username admin@org with password p#ss? becomes http://admin%40org:p%23ss%3F@host:8123/database.
Tools and resources
All tools accept an optional profile; when omitted, the default profile is used.
Tools
Tool | Description | Key params |
| List configured connection profiles. Call first when picking a non-default profile. Returns | — |
| Execute one read-only |
|
|
|
|
| Execute one write statement (DDL/DML). Advertised only when some profile sets |
|
types—EXPLAINvariants:plan(indexes),pipeline,syntax. Defaults toplanandpipeline.parameters— Named parameters for driver placeholders,%(name)sor{name:Type}.database— Session default database for unqualified names; otherwise qualify asdb.table.
Catalog discovery has no dedicated tool: list databases, tables and columns — and read sizes (total_rows, total_bytes) and keys (primary_key, sorting_key, partition_key) — with run_query over system.databases, system.tables and system.columns, which take ordinary WHERE predicates where SHOW takes only LIKE. SHOW earns its place for DDL a listing cannot give you — SHOW CREATE TABLE/VIEW/DICTIONARY for codecs, TTLs and the full column list.
Results are RFC 4180 CSV: the first row is the header, the rest are data. NULL is written as \N, ClickHouse's own CSV null representation, so it stays distinct from the empty string.
A plan's Indexes section is not authoritative about a table's keys: it names only the key columns the query used, so a query that skips the leading key column reports a shorter key than the table has. Confirm from system.tables, which answers in a few dozen tokens where SHOW CREATE TABLE spends several hundred to say the same thing.
The row caps that applied to a call arrive with its result as truncated and row_limit.
Resources
URI | Description |
| List configured connection profiles, including |
| Fetch a query result snapshot as CSV; |
Security
Every client this server opens carries ClickHouse's own readonly=1, so the engine — not just the server's SQL checks — refuses:
writes of any kind (
INSERT, DDL,ALTER … UPDATE,SYSTEM,GRANT);the external table functions
url(),s3(),remote(),mysql()and friends, so a query cannot reach a host outside the configured profile;query-level
SETTINGS, so the row and time caps cannot be raised by the SQL an agent supplies, andINTO OUTFILEis refused.
readonly=2 is deliberately not used: it permits SETTINGS changes, which would make those caps advisory. The tradeoff is that benign per-query tuning (SETTINGS max_threads = …) is refused too.
On top of that, run_query accepts SELECT / WITH … SELECT / SHOW and analyze_query only the first two, one statement per call. Interactive queries enforce a tight row cap (default 500, hard ceiling 1 000); for larger extracts use snapshot=true (default 10 000, hard ceiling 50 000).
Writes are opt-in, and invisible until then. run_command runs on a client carrying readonly=0, so it executes arbitrary DDL and DML — and, with readonly lifted, the external table functions come back too. Unless at least one configured profile sets ALLOW_WRITE (default false), the tool is not registered at all: it never appears in tools/list, so a read-only deployment spends no context on it and offers no write surface an agent could be talked into. Once any profile opts in, the tool is advertised server-wide and is still refused at call time on profiles that remain locked; list_profiles reports allow_write per profile so an agent can pick a writable one.
ALLOW_WRITE is a soft, application-level guard, not a security boundary — it constrains this server, not the database. For a genuine read-only guarantee, connect with a login whose ClickHouse grants stop at SELECT, and keep write-enabled profiles pointed at credentials scoped to only what they need. run_command carries destructive and openWorld tool annotations so hosts can gate it behind confirmation, but honoring those annotations is the host's choice. ClickHouse has no transaction to roll back in here: a statement that lands, stays.
Use environment variables or the config file for connection credentials — never commit secrets.
MCP host examples
Snippets use uvx mcp-clickhousex (no clone required; ensure uv is on your PATH). Replace connection details as needed; the env block is unnecessary when the DSN already comes from config.json or the environment.
Claude Code and Cursor read the same mcpServers shape:
{
"mcpServers": {
"clickhouse": {
"command": "uvx",
"args": ["mcp-clickhousex"],
"env": {
"MCP_CLICKHOUSE_DSN": "http://default:@localhost:8123/default"
}
}
}
}Codex (TOML):
[mcp_servers.clickhouse]
command = "uvx"
args = ["mcp-clickhousex"]
[mcp_servers.clickhouse.env]
MCP_CLICKHOUSE_DSN = "http://default:@localhost:8123/default"OpenCode:
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"clickhouse": {
"type": "local",
"enabled": true,
"command": ["uvx", "mcp-clickhousex"],
"environment": {
"MCP_CLICKHOUSE_DSN": "http://default:@localhost:8123/default"
}
}
}
}GitHub Copilot:
{
"inputs": [],
"servers": {
"clickhouse": {
"type": "stdio",
"command": "uvx",
"args": ["mcp-clickhousex"],
"env": {
"MCP_CLICKHOUSE_DSN": "http://default:@localhost:8123/default"
}
}
}
}Tests
Tests require a running ClickHouse instance; the suite creates a sample table in the default database, seeds it, and drops it after.
uv run pytest tests/ -vThe harness locates the instance through MCP_TEST_CLICKHOUSE_DSN, falling back to http://admin:password123@localhost:8123/default. Set it to point tests at another server without touching your production MCP_CLICKHOUSE_DSN.
The suite configures two profiles on that one instance — a read-only default and a write-enabled writable — so both halves of the write gate are exercised: run_command is advertised because a profile opts in, and is still refused against the profile that does not.
Contributing
Open issues or PRs; follow existing style and add tests where appropriate.
License
Available Tools
8 toolsanalyze_queryARead-only
[ClickHouse] Explain read-only SELECT or WITH … SELECT.
Returns plan, pipeline, and/or syntax text. Default types plan and pipeline. Uses query timeout and optional database; no max-rows cap unlike run_query.
| Name | Required | Description | Default |
|---|---|---|---|
| sql | Yes | Read-only SELECT or WITH … SELECT for EXPLAIN. One statement; same validation as run_query. | |
| types | No | EXPLAIN variants: plan (indexes), pipeline, syntax. Default plan and pipeline if omitted. | |
| profile | No | Profile name; uses default profile when omitted. Src: profiles. | |
| database | No | Session default database for unqualified names. Src: databases. | |
| parameters | No | Named parameters for driver placeholders (e.g. %(name)s or {name:Type}). |
Output Schema
| Name | Required | Description |
|---|---|---|
| plan | No | EXPLAIN PLAN output. |
| syntax | No | EXPLAIN SYNTAX output. |
| pipeline | No | EXPLAIN PIPELINE output. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds behavioral context beyond readOnlyHint and openWorldHint annotations, such as query timeout, optional database, and the absence of max-rows cap. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences, front-loaded with core purpose, and each sentence provides distinct information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given output schema existence and high parameter coverage, description covers key aspects: purpose, defaults, and comparison. Minor missing details like timeout value are acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds value by specifying default types (plan and pipeline) and mentioning query timeout, which is not in schema. Slight improvement over baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool performs EXPLAIN on read-only SELECT/WITH SELECT, returning plan/pipeline/syntax. Distinguishes from sibling run_query by noting no max-rows cap.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides context on when to use (for EXPLAIN) and comparison to run_query. Implicitly limits to read-only queries but lacks explicit alternatives for DDL or other analysis tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_cluster_propertiesARead-only
[ClickHouse] Get cluster properties and execution limits.
Returns ClickHouse server version plus enforced limits (max rows, timeouts) for the profile.
| Name | Required | Description | Default |
|---|---|---|---|
| profile | No | Profile name; uses default profile when omitted. Src: profiles. |
Output Schema
| Name | Required | Description |
|---|---|---|
| limits | Yes | |
| version | Yes | ClickHouse server version string. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, and the description adds context about specific returned data (version, limits). No contradiction. Does not mention any side effects or authorization needs, but read-only nature covers safety.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff. First sentence states purpose, second describes output. Information is front-loaded and every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present and simple input, the description provides all necessary context. Annotations cover safety, and the description adequately explains the tool's scope and return content.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and describes the profile parameter well. The description does not add extra details beyond the schema, which is adequate for a single optional parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Get cluster properties and execution limits' and specifies it returns 'ClickHouse server version plus enforced limits', which is a specific verb and resource. It distinguishes from sibling tools like run_query and list_profiles.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage as a read-only check for server properties and limits, but no explicit when-to-use or when-not-to-use guidance compared to siblings like list_profiles.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_columnsARead-only
[ClickHouse] List columns for a table or view.
Rows from system.columns for the resolved database and table.
| Name | Required | Description | Default |
|---|---|---|---|
| table | Yes | Table or view name, or database.table. Src: tables. | |
| profile | No | Profile name; uses default profile when omitted. Src: profiles. | |
| database | No | Database when table is unqualified; ignored if table contains a dot. Client default when omitted. Src: databases. |
Output Schema
| Name | Required | Description |
|---|---|---|
| rows | Yes | Row values aligned with the columns list. |
| columns | Yes | Ordered list of column names. Each row aligns with these names by index. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, so the description's mention of using system.columns adds some context but does not reveal additional behavioral traits beyond what annotations provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with just two sentences, no redundancy, and the key purpose is front-loaded. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only list tool with full parameter documentation, an output schema, and clear annotations, the description sufficiently covers the context and functionality without needing to explain return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the tool description does not add any extra meaning beyond the existing parameter descriptions, such as explaining the 'Src' references or providing examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List columns for a table or view' with a specific verb and resource. It includes the context '[ClickHouse]' and mentions the data source 'Rows from system.columns', making it distinct from sibling tools like list_tables or list_databases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for listing columns of a table or view, but it does not provide explicit guidance on when to use this tool vs alternatives, nor does it mention any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_databasesBRead-only
[ClickHouse] List databases.
Rows from system.databases visible to the connection.
| Name | Required | Description | Default |
|---|---|---|---|
| profile | No | Profile name; uses default profile when omitted. Src: profiles. |
Output Schema
| Name | Required | Description |
|---|---|---|
| rows | Yes | Row values aligned with the columns list. |
| columns | Yes | Ordered list of column names. Each row aligns with these names by index. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true. Description adds the detail that it queries system.databases and depends on connection visibility. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, no wasted words, front-loaded with purpose and context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with one optional parameter and an output schema, the description is adequate. Provides source table and visibility context, but could mention output shape briefly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter 'profile' already documented. Description adds no extra meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'List' and resource 'databases', includes context '[ClickHouse]' and source 'system.databases'. Differentiates from siblings like 'list_tables' implicitly but no explicit distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Mentions that rows are from system.databases and visible to the connection, but provides no guidance on when to use this tool vs alternatives like list_tables or run_show. Lacks explicit when-to-use or when-not-to-use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_profilesARead-only
[ClickHouse] List configured profiles.
Each entry includes name and optional description.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds value beyond annotations by specifying that output includes name and optional description. Annotations already declare readOnlyHint=true, so the read-only nature is known. No additional behavioral traits (e.g., ordering, filtering) are disclosed, but the description does not contradict annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences that front-load the purpose and follow with a key output detail. Every word earns its place with no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and the presence of an output schema, the description is mostly complete. It explains what the tool does and what output to expect. It could optionally mention the source of profiles (e.g., system.profiles), but the current level is adequate for a simple listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no parameters, so schema description coverage is 100%. The description does not need to add parameter semantics. It provides a baseline adequate for a parameterless tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List configured profiles') and the resource ('profiles'). The output details are mentioned (name and optional description). However, it does not explicitly differentiate from sibling list tools (e.g., list_databases, list_tables) beyond the resource name, lacking a contrastive statement.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, common use cases, or when not to use it. The tool is simple, but the description does not help an agent decide between this and other list tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_tablesARead-only
[ClickHouse] List tables and views in a database.
Rows from system.tables: name, engine, primary_key, sorting_key, partition_key, total_rows, total_bytes for query planning.
| Name | Required | Description | Default |
|---|---|---|---|
| profile | No | Profile name; uses default profile when omitted. Src: profiles. | |
| database | No | Database to list; client default when omitted. Src: databases. |
Output Schema
| Name | Required | Description |
|---|---|---|
| rows | Yes | Row values aligned with the columns list. |
| columns | Yes | Ordered list of column names. Each row aligns with these names by index. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds context about the specific columns returned. However, it does not disclose any behavioral traits beyond that, but given the annotations, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two sentences that front-load the purpose and return value. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only list tool with an output schema and well-documented parameters, the description is nearly complete. A minor gap: it does not clarify behavior when database is omitted (client default), but overall it is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters (profile, database). The description does not add extra meaning beyond what the schema provides, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists tables and views in a database, specifying the source (system.tables) and the columns returned. It effectively distinguishes from sibling tools like list_databases and list_columns by focusing on tables.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., run_show or analyze_query). The description merely states functionality without providing context on preferred scenarios or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
run_queryARead-only
[ClickHouse] Execute read-only SELECT or WITH … SELECT.
One statement; DML, DDL, SET, SYSTEM, and similar are rejected. Max-rows cap; overflow sets truncated and row_limit. Same SQL validation as analyze_query.
Returns {data, row_count} where data is an RFC 4180 CSV string.
Pass snapshot=true to persist the result to disk and receive a
{snapshot_uri, row_count} instead; fetch the CSV via the snapshot
resource URI.
| Name | Required | Description | Default |
|---|---|---|---|
| sql | Yes | Read-only SELECT or WITH … SELECT. One statement; use qualified db.table or database. Driver placeholder syntax for parameters. | |
| profile | No | Profile name; uses default profile when omitted. Src: profiles. | |
| database | No | Session default database for unqualified names. Src: databases. | |
| snapshot | No | When true, persist the full result as a CSV file and return a resource URI (chx://snapshots/{id}) instead of inline data. Use for queries that may exceed the interactive row limit (1 000). Snapshot limits apply (default 10 000 rows, hard ceiling 50 000). Entries expire after 7 days. | |
| parameters | No | Named parameters for driver placeholders (e.g. %(name)s or {name:Type}). |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true and openWorldHint=true. Description aligns fully and adds rich behavioral details: max-rows cap, truncation with row_limit flag, CSV return format, snapshot persistence with expiration and limits. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is a single, well-structured paragraph with each sentence serving a distinct purpose: resource and verb, constraints, limits, return format, and snapshot alternative. No fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 5 parameters, 100% schema coverage, and an output schema (not shown but indicated), the description covers purpose, constraints, limits, return format, and snapshot behavior comprehensively. No gaps given the context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% description coverage, but description adds value by explaining the return format (CSV string and snapshot URI pattern) which is not in the input schema. Also reiterates constraints on sql parameter. Overall meaningfully supplements schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it executes read-only SELECT or WITH SELECT on ClickHouse. It specifies the resource ([ClickHouse] queries) and verb (execute read-only). Distinguishes from siblings like run_show and analyze_query by stating specific SQL types and validation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states that only read-only queries are allowed, and DML/DDL/SET etc. are rejected. Mentions same validation as analyze_query, linking to a sibling. Clear context for when to use, but does not explicitly exclude alternatives or provide when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
run_showARead-only
[ClickHouse] Execute SHOW introspection statement.
One statement per call; INTO OUTFILE rejected. Interactive row limits apply (default 500, hard ceiling 1 000). Same timeout as run_query.
| Name | Required | Description | Default |
|---|---|---|---|
| sql | Yes | Single SHOW statement (e.g. SHOW DATABASES, SHOW CREATE TABLE). No INTO OUTFILE. | |
| profile | No | Profile name; uses default profile when omitted. Src: profiles. | |
| database | No | Session default database for unqualified names. Src: databases. | |
| parameters | No | Named parameters for driver placeholders (e.g. %(name)s or {name:Type}). |
Output Schema
| Name | Required | Description |
|---|---|---|
| rows | Yes | Row values aligned with the columns list. |
| columns | Yes | Ordered list of column names. Each row aligns with these names by index. |
| row_limit | No | The enforced maximum number of rows returned for this query. |
| truncated | No | Whether the result set was truncated due to the enforced row limit. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark as read-only, and the description adds critical behavioral details: row limits (500 default, 1000 hard ceiling), INTO OUTFILE rejection, and timeout alignment with run_query. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each earning its place: purpose, constraints on statement, limits. Front-loaded and efficient with zero redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description sufficiently covers all behavioral aspects for a read-only introspection tool. Includes limits, timeout, and statement restrictions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds value by explaining the sql parameter constraint (single statement, no INTO OUTFILE) and implicitly relates to row limits. Modest but helpful addition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it executes SHOW introspection statements, distinguishing from siblings like run_query. It specifies constraints (single statement, no INTO OUTFILE), making the purpose specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context for when to use (SHOW statements) and constraints (row limits, timeout). Lacks explicit when-not-to-use alternatives, but the sibling tool names imply run_query for other queries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
8 tool updates
v0.8.0- First observed
analyze_query - First observed
get_cluster_properties - First observed
list_columns - First observed
list_databases - First observed
list_profiles - First observed
list_tables - First observed
run_query - First observed
run_show
TDQS
Scored across 8 tools
Each tool has a distinct purpose: listing profiles, cluster properties, running SELECT queries, running SHOW statements, analyzing queries, and listing databases, tables, and columns. No overlap in functionality.
Uses snake_case consistently, but mixes verb prefixes: 'list_', 'get_', 'run_', 'analyze_'. The pattern is somewhat predictable within categories (metadata listing uses 'list_', execution uses 'run_'), but not fully uniform.
8 tools is well-scoped for a read-only ClickHouse client. Covers metadata discovery, query execution, and analysis without unnecessary tools.
Covers essential read-only operations: metadata listing, SELECT, SHOW, and EXPLAIN. Lacks DDL/DML support, but that is intentional. Minor gap: no tool to retrieve table DDL or status.
Maintenance
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