MCP DevOps Kit
Click on "Install 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 DevOps Kitlist my GitHub repositories"
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.
CodeBlueprint — MCP Servers
Model Context Protocol (MCP) servers for AI coding agents by CodeBlueprint.
Available Servers
mcp-devops-kit
GitHub, Docker, and filesystem tools for AI coding agents. View on GitHub: https://github.com/Jmfrodero/codeblueprint-mcp/tree/main/devops-kit
Related MCP server: GitHub MCP Server
Roadmap
mcp-docs-generator (in development)
mcp-spain-tools (planned)
Available Tools
9 toolsdocker_logsB
Get logs from a Docker container
| Name | Required | Description | Default |
|---|---|---|---|
| container_id | Yes | Container ID or name | |
| lines | No | Number of lines to fetch (default 100) | |
| tail | No | Show last N lines (default: all) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must convey behavioral traits, but it only states the basic function. It does not disclose whether logs are streamed or fetched, the output format, error behavior, or permissions required.
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 very short (6 words), which is concise but overly minimal. It is not wasteful, but it sacrifices useful detail for brevity, making it only adequately structured.
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 multiple parameters and no output schema, the description is incomplete. It lacks context on output format, behavior with different parameters, and error conditions, leaving the agent needing to infer from parameter descriptions alone.
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 already describes all three parameters with 100% coverage, so the description does not need to add details. However, it adds no additional meaning beyond the schema, meeting the baseline for high schema coverage.
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 (Get) and the resource (logs from a Docker container). It distinguishes from sibling tools like docker_ps (list containers) and docker_stats (show stats), which have different purposes.
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 usage guidelines or context are provided. The description does not indicate when to use this tool versus alternatives like docker_ps or docker_stats, nor does it mention prerequisites or typical scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
docker_psB
List running Docker containers
| Name | Required | Description | Default |
|---|---|---|---|
| all | No | Show all containers (default shows just running) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must fully convey behavioral traits. It fails to mention that the tool is read-only, requires a running Docker daemon, or what the output format is. Simply stating 'list' implies a read operation but is insufficient.
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 a single concise sentence that immediately states the tool's purpose. Every word earns its place with no wasted text.
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 tool with one boolean parameter and no output schema, the description is adequate but lacks mention of output format (e.g., container IDs, names) and prerequisites (e.g., Docker daemon running). It does not fully prepare the agent for invoking the tool correctly.
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 covers the single parameter 'all' with full description (100% coverage). The tool description does not add meaning beyond the schema; it merely restates the concept of 'running' containers. Baseline 3 is appropriate.
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 'List running Docker containers' uses a specific verb (List) and resource (running Docker containers), clearly distinguishing it from sibling tools like docker_logs (logs) and docker_stats (stats).
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 such as docker_logs or docker_stats. The description does not include context about prerequisites or intended use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
docker_statsB
Get resource statistics for containers
| Name | Required | Description | Default |
|---|---|---|---|
| container_id | No | Container ID or name (optional for all) | |
| stream | No | Stream statistics (default: false) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only states 'get resource statistics' without explaining what the statistics include, whether the container must be running, or the effect of the 'stream' parameter. This lack of detail leaves significant gaps for an agent.
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 a single sentence, front-loaded with the verb 'Get'. It contains no redundant words and is appropriately sized for the stated purpose. Every word earns its place.
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 tool has two parameters, no output schema, and no annotations, the description is incomplete. It does not explain the return format, the meaning of 'statistics', or how streaming works. The agent would lack essential context for correct invocation.
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 the schema already documents both parameters. The description adds no extra meaning beyond 'statistics', failing to explain how container_id and stream affect the operation. Baseline 3 is appropriate as the description does not degrade but does not enhance.
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 gets resource statistics for containers, distinguishing it from sibling tools like docker_logs (logs) and docker_ps (listing). However, it does not specify what resource statistics entails (e.g., CPU, memory), which could be more precise.
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 when to use this tool—to get resource statistics—but provides no explicit guidance on when not to use it or how it compares to alternatives like docker_ps or docker_stats (itself). There is no mention of prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
fs_lsC
List directory contents
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Directory path to list |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only states 'List directory contents' without specifying what is included (e.g., hidden files, metadata) or error handling (e.g., path not found). This is insufficient.
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 concise and front-loaded, containing no unnecessary words. However, it sacrifices completeness for brevity, making it slightly under-specified.
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 low complexity (single string parameter, no output schema), the description is minimally adequate but omits what exactly is returned (e.g., names, full paths, metadata). More context would improve completeness.
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 covers 100% of parameters with a clear description for 'path'. The tool description does not add any additional meaning beyond the schema, so baseline 3 is appropriate.
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) and resource (directory contents), distinguishing it from sibling tools like fs_read (file contents) and fs_stats (file stats). However, it lacks explicit differentiation or scope details.
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 usage guidelines are provided. The description does not indicate when to use this tool versus 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.
fs_readC
Read file contents
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | File path to read | |
| max_lines | No | Maximum number of lines to read (default: 1000) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral traits. It only states what it does (read file contents) but does not disclose any limitations (e.g., text vs binary, encoding, file size limits) or side effects (none expected).
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 (one short sentence), which is efficient but borderline under-specified. It front-loads the purpose but lacks detail that could be added without verbosity.
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 tool has two parameters, no output schema, and no annotations, the description is too minimal. It does not explain what the tool returns (e.g., file content as string) or how max_lines affects behavior. A more complete description would clarify return format and default behavior.
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 covers both parameters with descriptions (path and max_lines). The description does not add any additional meaning beyond what the schema already provides, so baseline 3 is appropriate.
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 'Read file contents' clearly identifies the verb (Read) and resource (file contents), but it does not explicitly distinguish itself from siblings like fs_ls or fs_stats. However, given the simplicity of the tool and the family, the purpose is clear enough.
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 provides no guidance on when to use this tool versus alternatives (e.g., fs_ls for directory listing, docker_logs for container logs). No exclusions or context hints are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
fs_statsB
Get file or directory statistics
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Path to get statistics for |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden. It only states the basic purpose without disclosing behavior on missing paths, permissions, error handling, or what 'statistics' includes. Minimal transparency.
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 a single, direct sentence with no wasted words. It is efficient, though slightly more context could be added without sacrificing conciseness.
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 tool's simplicity (1 param, no output schema), the description is too minimal. It fails to explain what statistics are returned (e.g., size, modification time), leaving the agent uninformed about the tool's output.
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 details the single 'path' parameter. The description adds no extra meaning beyond the schema, resulting in a baseline score of 3.
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 'Get file or directory statistics' clearly states the verb (Get) and resource (file or directory statistics), and distinguishes from sibling tools like fs_ls (list contents) and fs_read (read content).
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 vs alternatives, no when-not-to-use conditions, and no mention of prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
github_create_issueB
Create a new issue on a GitHub repository
| Name | Required | Description | Default |
|---|---|---|---|
| owner | Yes | Repository owner | |
| repo | Yes | Repository name | |
| title | Yes | Issue title | |
| body | No | Issue body/description | |
| labels | No | Issue labels |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states the creation action but does not disclose side effects, authentication requirements, rate limits, or error conditions. For a mutation tool, this is insufficient.
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 a single sentence with no redundancy. While concise, it misses opportunities to add value within the same length.
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 complexity (5 parameters, 3 required) and lack of output schema or annotations, the description is too minimal. It does not explain return values, success behavior, or potential errors, making it incomplete for an agent to fully understand the tool's behavior.
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 input schema already documents all 5 parameters. The description adds no additional meaning, examples, or constraints, meeting the baseline for full schema coverage.
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 verb 'Create' and the resource 'a new issue on a GitHub repository'. It is specific and distinct from sibling tools like github_get_repo_info or github_list_repos, which are for read operations.
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 provides no guidance on when to use this tool, when not to use it, or alternatives. It only states the function without contextual usage information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
github_get_repo_infoB
Get information about a GitHub repository
| Name | Required | Description | Default |
|---|---|---|---|
| owner | Yes | Repository owner | |
| repo | Yes | Repository name |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; the description only states 'get information' without detailing what information is returned, authentication needs, or rate limits.
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?
Single sentence with no wasted words, but could benefit from more detail without being overly long.
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 no output schema and sibling tools, the description is too sparse; it fails to describe the return value or any additional 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?
Schema covers 100% of parameters with descriptions; the tool description adds no additional meaning beyond what the schema already provides.
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 uses a specific verb 'Get' and resource 'repository', clearly distinguishing it from sibling tools like 'github_create_issue' (create) and 'github_list_repos' (list multiple).
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, and no exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
github_list_reposA
List repositories for a GitHub user or organization
| Name | Required | Description | Default |
|---|---|---|---|
| owner | Yes | The GitHub username or organization name | |
| type | No | Filter by repository type: all, owner, public, private | owner |
| per_page | No | Number of results per page (max 100) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description lacks behavioral details such as pagination handling, authentication needs, rate limits, or response structure. The schema hints at pagination via `per_page`, but the description does not mention this.
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 a single sentence with no wasted words, concisely conveying the core purpose.
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 lack of output schema and annotations, the description is minimal. It does not explain the output format or pagination behavior, leaving gaps for the agent to infer. Adequate but could be more informative.
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 the schema already describes each parameter. The description adds no additional meaning beyond what is in the schema; it merely restates that the tool lists repos for a user or org.
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 verb 'List' and the resource 'repositories for a GitHub user or organization', which is specific and distinguishes it from siblings like `github_get_repo_info` for a single repo.
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 repos for a user/org but does not explicitly state when to use this tool versus alternatives like `github_get_repo_info` or when not to use it.
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. Dates show when Glama detected each change.
9 tool updates
v1.0.0- First observed
docker_logs - First observed
docker_ps - First observed
docker_stats - First observed
fs_ls - First observed
fs_read - First observed
fs_stats - First observed
github_create_issue - First observed
github_get_repo_info - First observed
github_list_repos
TDQS
Each tool targets a clear and distinct operation: Docker tools cover logs, listing, and stats; filesystem tools cover listing, reading, and stats; GitHub tools cover issue creation, repo info, and repo listing. No overlap across categories.
All tools follow a consistent domain_verb_noun pattern (e.g., docker_logs, fs_ls, github_create_issue), making it easy to infer action and scope from the name.
With 9 tools across three well-defined domains, the count is within the optimal range (3–15). Each tool serves a distinct purpose without redundancy.
The tool set covers only monitoring and basic read operations for Docker and filesystem, and minimal GitHub actions. Missing fundamental operations like container management, file writes, GitHub issues listing/updating, and PR handling. This is a significant gap for a 'DevOps Kit'.
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