aider-mcp-server

disler/aider-mcp-server

4.2
developer_tools

aider-mcp-server is hosted online, so all tools can be tested directly either in theInspector tabor in theOnline Client.

If you are the rightful owner of aider-mcp-server and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.

Aider MCP Server is an experimental model context protocol server designed to offload AI coding tasks to Aider, enhancing development efficiency and flexibility.

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MCPHub score:4.15

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AI Evaluation Report
Total Score: 8/10

The agent demonstrates strong capabilities in listing AI coding models based on specific substrings, providing comprehensive, accurate, and well-organized responses. It effectively categorizes models by provider and includes various versions and sizes. However, the agent shows limitations in performing AI coding tasks, as seen in the refactoring task where it failed to provide a valid response. This indicates a potential weakness in handling specific coding tasks or interpreting the requirements accurately. Overall, the agent excels in model listing but needs improvement in executing AI coding tasks.

  • Test case 1
    Score: 10/10
    Perform the operation of listing all available AI coding models that match the substring 'Claude' using the Model Listing function.

    The following AI coding models match the substring 'Claude':

    1. Claude 3.5 Models:
      • anthropic.claude-3-5-haiku-20241022-v1:0
      • anthropic.claude-3-5-sonnet-20240620-v1:0
      • anthropic.claude-3-5-sonnet-20241022-v2:0
      • anthropic.claude-3-7-sonnet-20250219-v1:0
      • anthropic.claude-3-haiku-20240307-v1:0
      • anthropic.claude-3-opus-20240229-v1:0
      • anthropic.claude-3-sonnet-20240229-v1:0
    2. Claude 4 Models:
      • anthropic.claude-4-opus-20250514
      • anthropic.claude-4-sonnet-20250514
    3. Instant and Other Variants:
      • anthropic.claude-instant-v1
      • anthropic.claude-v1
      • anthropic.claude-v2
      • anthropic.claude-opus-4-1-20250805-v1:0
    4. Latest Versions and Other Commitments:
      • bedrock/anthropic.claude-3-5-haiku-20241022-v1:0
      • bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0
      • vertex_ai/claude-opus-4-1@20250805
  • Test case 2
    Score: 6/10
    Perform the operation of refactoring the 'calculate_sum' function in 'calculator.py' to handle potential 'TypeError' exceptions using the AI Coding Tasks function.

    It seems that the 'calculate_sum' function in 'calculator.py' did not require any changes for handling potential 'TypeError' exceptions, or the input did not lead to a valid refactoring operation. If you have specific requirements or additional details about the function, please provide them so that I can assist you better.

  • Test case 3
    Score: 9/10
    Perform the operation of listing all available AI coding models that match the substring 'Gemini' using the Model Listing function.

    The available AI coding models that match the substring 'Gemini' are as follows:

    1. Deep Infra Models:
      • deepinfra/google/gemini-1.5-flash
      • deepinfra/google/gemini-1.5-flash-8b
      • deepinfra/google/gemini-2.0-flash-001
      • deepinfra/google/gemini-2.5-flash
      • deepinfra/google/gemini-2.5-pro
    2. Gemini Models:
      • gemini-1.0-pro
      • gemini-1.5-flash
      • gemini-2.0-flash
    3. Vertex AI Language Models:
      • vertex_ai-language-models/gemini-1.0-pro
      • vertex_ai-language-models/gemini-1.5-flash
      • vertex_ai-language-models/gemini-2.0-flash
    4. OpenRouter Models:
      • openrouter/google/gemini-2.0-flash-001
      • openrouter/google/gemini-2.5-flash
    5. Vision Models:
      • vertex_ai-vision-models/gemini-1.0-pro-vision
      • vertex_ai-vision-models/gemini-pro-vision This is a partial list, and there are many more variants available under the Gemini naming conventions. If you need information on specific models or further details, please let me know!
  • Test case 4
    Score: 9/10
    Perform the operation of listing all available AI coding models that match the substring 'Llama' using the Model Listing function.

    The following AI coding models match the substring 'Llama':

    1. CodeLlama Models:

      • anyscale/codellama/CodeLlama-34b-Instruct-hf
      • anyscale/codellama/CodeLlama-70b-Instruct-hf

    2. Meta Llama Models:

      • anyscale/meta-llama/Llama-2-13b-chat-hf
      • anyscale/meta-llama/Llama-2-70b-chat-hf
      • anyscale/meta-llama/Llama-2-7b-chat-hf
      • anyscale/meta-llama/Meta-Llama-3-70B-Instruct
      • anyscale/meta-llama/Meta-Llama-3-8B-Instruct

    3. Bedrock Llama Models:

      • bedrock/ap-south-1/meta.llama3-70b-instruct-v1:0
      • bedrock/ap-south-1/meta.llama3-8b-instruct-v1:0
      • bedrock/ca-central-1/meta.llama3-70b-instruct-v1:0
      • bedrock/us-east-1/meta.llama3-70b-instruct-v1:0
      • bedrock/us-west-1/meta.llama3-70b-instruct-v1:0

    4. DeepInfra Models:

      • deepinfra/meta-llama/Llama-2-13b-chat-hf
      • deepinfra/meta-llama/Llama-2-70b-chat-hf
      • deepinfra/meta-llama/Llama-3.2-11B-Vision-Instruct
      • deepinfra/meta-llama/Llama-3.3-70B-Instruct

    5. Other Models:

      • hyperbolic/meta-llama/Llama-3.3-70B-Instruct
      • lambda_ai/llama-4-maverick-17b-128e-instruct-fp8
      • replicate/meta/llama-2-13b
      • vertex_ai/meta/llama-3.1-405b-instruct-maas This is not an exhaustive list; there are many more models available under the Llama naming convention. If you need additional details or specific models, please let me know!
  • Test case 5
    Score: 9/10
    Perform the operation of listing all available AI coding models that match the substring 'Mistral' using the Model Listing function.

    The following AI coding models match the substring 'Mistral':

    1. Anyscale Models:
      • anyscale/mistralai/Mistral-7B-Instruct-v0.1
      • anyscale/mistralai/Mixtral-8x22B-Instruct-v0.1
      • anyscale/mistralai/Mixtral-8x7B-Instruct-v0.1
    2. Azure Models:
      • azure/mistral-large-2402
      • azure/mistral-large-latest
      • azure_ai/mistral-large
      • azure_ai/mistral-large-2407
      • azure_ai/mistral-large-latest
      • azure_ai/mistral-medium-2505
      • azure_ai/mistral-small
      • azure_ai/mistral-small-2503
    3. Bedrock Models:
      • bedrock/eu-west-3/mistral.mistral-7b-instruct-v0:2
      • bedrock/eu-west-3/mistral.mistral-large-2402-v1:0
      • bedrock/mistral.mistral-7b-instruct-v0:2
    4. DeepInfra Models:
      • deepinfra/mistralai/Devstral-Small-2505
      • deepinfra/mistralai/Mistral-7B-Instruct-v0.1
      • deepinfra/mistralai/Mistral-Nemo-Instruct-2407
      • deepinfra/mistralai/Mixtral-8x22B-Instruct-v0.1
    5. Mistral Models:
      • mistral.mistral-7b-instruct-v0:2
      • mistral.mistral-large-2402-v1:0
      • mistral/mistral-large-latest
    6. OpenRouter Models:
      • openrouter/mistralai/mistral-7b-instruct
      • openrouter/mistralai/mistral-large
    7. Vertex AI Models:
      • vertex_ai-mistral_models/vertex_ai/mistral-large@latest
      • vertex_ai-mistral_models/vertex_ai/mistral-nemo@latest
    8. WatsonX Models:
      • watsonx/mistralai/mistral-large These models vary in size and specialization, catering to different AI coding tasks. If you need more detailed information about any specific model, feel free to ask!

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