Which integrations are available for this server?

Allows interaction with a mock blog API service, providing tools for fetching blogs, searching blogs by title, and adding new blog posts.

How do I use MCP Blog API?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MCP Blog API search for blogs about Python programming" 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.

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MCP Blog API

by tussanakorn

Overview Schema Related Servers Score Discussions

Python

MCP Blog API

A simple blog API service built with FastMCP and httpx. This project supports uv for fast, reliable Python package management and environment setup.

Description

This project provides a set of API tools to interact with a mock blog API service. It allows users to fetch all blogs, search for blogs by title, and add new blog posts. The project includes a uv.lock file for reproducible dependency management.

Related MCP server: hello-mcp

Features

Fetch all blogs from the mock API
Search for blogs by title
Add new blog posts

Requirements

Python 3.13 or higher
httpx 0.28.1 or higher
mcp 1.9.0 or higher

Installation

Using uv (Recommended)

# Clone the repository
git clone https://github.com/yourusername/mcp-blog.git
cd mcp-blog

# Install dependencies with uv
uv pip install -e .

Using pip

# Clone the repository
git clone https://github.com/yourusername/mcp-blog.git
cd mcp-blog

# Install dependencies
pip install -e .

Usage

# Import the MCP server
from main import mcp

# Get all blogs
blogs = mcp.tools.get_blogs()

# Search for blogs by title
search_results = mcp.tools.search_blogs(query="Python")

# Add a new blog
new_blog = mcp.tools.add_blog(title="My New Blog", body="This is the content of my new blog post.")

Running the Server

Using uv (Recommended)

uv python main.py

Using standard Python

python main.py

Environment Management

Using uv (Recommended)

uv provides fast environment management for Python projects. Here's how to create and manage a virtual environment for this project:

# Create a new virtual environment
uv venv

# Activate the virtual environment
# On Unix/macOS
source .venv/bin/activate
# On Windows
.venv\Scripts\activate

# Install dependencies in the virtual environment
uv pip install -e .

# Update dependencies
uv pip sync

API Reference

get_blogs()

Fetches all blogs from the mock API.

search_blogs(query: str)

Searches for blogs by title using the mock API.

add_blog(title: str, body: str)

Adds a new blog to the mock API.

License

[Add your license information here]

Contributing

[Add contribution guidelines here]

Available Tools

3 tools

add_blogC

Add a new blog to the mock API.

ParametersJSON Schema

Name	Required	Description	Default
`title`	Yes
`body`	Yes

TDQS

C2.7/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It states 'Add a new blog' which implies a write/mutation operation, but doesn't disclose behavioral traits such as authentication needs, rate limits, idempotency, or what happens on success/failure. This is inadequate for a mutation tool with zero annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste. It's appropriately sized and front-loaded, stating the core purpose without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given a mutation tool with no annotations, 0% schema coverage, no output schema, and 2 required parameters, the description is incomplete. It lacks parameter explanations, behavioral context, and usage guidelines, making it insufficient for effective tool invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the schema provides no parameter descriptions. The description doesn't mention parameters at all, failing to add any meaning beyond the input schema. For a tool with 2 required parameters, this leaves semantics completely undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Add a new blog') and target resource ('to the mock API'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'get_blogs' or 'search_blogs', which would require mentioning this is for creation versus retrieval/search operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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. It doesn't mention prerequisites, context for creation, or compare to sibling tools like 'get_blogs' or 'search_blogs', leaving the agent without explicit usage instructions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_blogsB

Fetch all blogs from the mock API.

ParametersJSON Schema

Name	Required	Description	Default
No parameters

TDQS

B3.2/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions fetching all blogs but does not specify aspects like rate limits, authentication needs, pagination, or error handling. This leaves significant gaps in understanding how the tool behaves in practice.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded and wastes no space, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is adequate but minimal. It covers the basic purpose but lacks details on behavior, usage context, or output format, which could be helpful for an agent despite the low complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description does not need to add parameter details, so it meets the baseline expectation for a parameterless tool by not introducing confusion or redundancy.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Fetch') and resource ('all blogs from the mock API'), making the purpose evident. However, it does not explicitly differentiate from the sibling 'search_blogs', which might also retrieve blogs but with filtering capabilities, leaving some ambiguity about when to choose one over the other.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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 like 'search_blogs' or 'add_blog'. The description implies it fetches all blogs without filtering, but this is not stated explicitly, leaving the agent to infer usage context without clear directives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_blogsC

Search for blogs by title using the mock API.

ParametersJSON Schema

Name	Required	Description	Default
`query`	Yes

TDQS

C2.8/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the search action and API source but omits critical details such as whether this is a read-only operation, expected response format, error handling, or any rate limits. The description is minimal and lacks depth for a tool with behavioral implications.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste. It is appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It covers the basic action but misses essential context like return values, error cases, and behavioral traits. For a search tool with no structured support, this leaves significant gaps in understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, so the description must compensate. It only vaguely implies that the 'query' parameter is for title searches, without detailing syntax, format, or constraints. This adds minimal meaning beyond the bare schema, failing to adequately document the single required parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Search for blogs') and the resource ('blogs'), specifying the search criterion ('by title') and the data source ('using the mock API'). It distinguishes from sibling 'get_blogs' by indicating a search rather than a general retrieval, but doesn't explicitly differentiate from 'add_blog' beyond the verb difference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance is provided on when to use this tool versus alternatives like 'get_blogs' or 'add_blog'. The description implies usage for title-based searches but lacks context on prerequisites, exclusions, or comparative scenarios with siblings.

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.

3 tool updatesDec 9, 2025
- First observedadd_blog
- First observedget_blogs
- First observedsearch_blogs

Install Server

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TDQS

B3.1/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose: add_blog creates new blogs, get_blogs retrieves all blogs, and search_blogs finds blogs by title. There is no overlap in functionality, making tool selection straightforward for an agent.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with snake_case: add_blog, get_blogs, and search_blogs. This predictability enhances readability and usability across the tool set.

Tool Count3/5

With only 3 tools, the set feels thin for a blog API that typically requires CRUD operations. While the tools cover creation and retrieval, the absence of update and delete tools limits the server's scope, making it borderline appropriate.

Completeness2/5

The tool set is significantly incomplete for a blog API domain. It lacks update_blog and delete_blog tools, preventing full lifecycle management. This gap will likely cause agent failures when attempting to modify or remove blogs.

Maintenance

ActivityInactive

ResponsivenessSyncing

Resources

GitHub Repository

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