MCP server intelligence profile

Fabric MCP Server

Bridge between Fabric AI framework and MCP applications, enabling use of Fabric patterns and models in MCP-compatible environments like IDEs

Local Onlyksylvan
Awaiting current scanPypi · 1.2.1

The selected current version does not yet have completed public verification. Unknown does not mean clean or vulnerable.

1Distribution channel
6Independently observed tools
0Linked remote endpoints
AvailableVersion intelligence

Detailed security scan evidence is not public for this MCP yet. Public identity, registry metadata, and independently observed protocol inventory remain available.

Install and connect

Installation and connection instructions are shown only when supported by retained package, repository, or endpoint evidence.

Install fabric-mcp from PyPI

Version 1.2.1 declares 1 executable entrypoint.

python -m pip install 'fabric-mcp==1.2.1'
uvx --from 'fabric-mcp==1.2.1' fabric-mcp
MCP client configuration example
{
  "mcpServers": {
    "fabric-mcp": {
      "command": "uvx",
      "args": [
        "--from",
        "fabric-mcp==1.2.1",
        "fabric-mcp"
      ]
    }
  }
}

Build from source

Clone the canonical public repository, then follow its version-specific setup documentation.

git clone https://github.com/ksylvan/fabric-mcp

Identity

Canonical slugfabric-mcp-server-a29cb133DeploymentLocal Only
Canonical packagepypi:fabric-mcpRepositoryhttps://github.com/ksylvan/fabric-mcp
First publishedMay 12, 2026Latest releaseMay 12, 2026
Last security verification—Classification confidence90%
PublicationDraftOfficial distributionNot verified

Distributions

ChannelIdentifierCurrent versionVersionsSource
pypifabric-mcp1.2.11Repository

Current release

PackageVersionPublished / observedInventorySecurity scan
pypifabric-mcp1.2.1CurrentMay 12, 20266 toolsSucceeded · 0 resources · 0 promptsEvidence restricted
Enterprise protection

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  • Historical evidence and API exports
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Current version evidence

No public current-version evidence is available yet.

Current protocol inventory

2025-06-18Negotiated protocol
Fabric MCP v1.2.1Server-reported name
6Capability groups
Sep 4, 2026Observed

Tools 6

ToolCategoryAnnotationsRisk
fabric_get_configurationRetrieve Fabric configuration with sensitive values redacted. Returns: dict[Any, Any]: Configuration key-value pairs with sensitive values redacted. Sensitive keys (matching *_API_KEY, *_TOKEN, *_SECRET, *_PASSWORD patterns) with non-empty values are replaced with "[REDACTED_BY_MCP_SERVER]". Empty sensitive values and all non-sensitive values are passed through unchanged. Raises: McpError: For any API errors, connection issues, or invalid responses.
Input schema
{
  "additionalProperties": false,
  "properties": {},
  "type": "object"
}
Output schema
{
  "additionalProperties": true,
  "type": "object"
}
——
fabric_get_pattern_detailsRetrieve detailed information for a specific Fabric pattern.
Input schema
{
  "additionalProperties": false,
  "properties": {
    "pattern_name": {
      "type": "string"
    }
  },
  "required": [
    "pattern_name"
  ],
  "type": "object"
}
Output schema
{
  "additionalProperties": {
    "type": "string"
  },
  "type": "object"
}
——
fabric_list_modelsRetrieve configured Fabric models by vendor.
Input schema
{
  "additionalProperties": false,
  "properties": {},
  "type": "object"
}
Output schema
{
  "additionalProperties": true,
  "type": "object"
}
——
fabric_list_patternsReturn a list of available fabric patterns.
Input schema
{
  "additionalProperties": false,
  "properties": {},
  "type": "object"
}
Output schema
{
  "properties": {
    "result": {
      "items": {
        "type": "string"
      },
      "type": "array"
    }
  },
  "required": [
    "result"
  ],
  "type": "object",
  "x-fastmcp-wrap-result": true
}
——
fabric_list_strategiesRetrieve available Fabric strategies.
Input schema
{
  "additionalProperties": false,
  "properties": {},
  "type": "object"
}
Output schema
{
  "additionalProperties": true,
  "type": "object"
}
——
fabric_run_patternExecute a Fabric pattern with input text and return output. This tool calls the Fabric API's /chat endpoint to execute a named pattern with the provided input text. Returns either complete output (non-streaming) or a generator of chunks (streaming) based on the stream parameter.
Input schema
{
  "additionalProperties": false,
  "properties": {
    "pattern_name": {
      "type": "string",
      "description": "The name of the fabric pattern to run (required)."
    },
    "input_text": {
      "default": "",
      "type": "string",
      "description": "The input text to be processed by the pattern (optional)."
    },
    "stream": {
      "default": false,
      "type": "boolean",
      "description": "Whether to stream the output. If True, returns a generator of"
    },
    "config": {
      "anyOf": [
        {
          "description": "Configuration for pattern execution parameters.",
          "properties": {
            "model_name": {
              "anyOf": [
                {
                  "type": "string"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            },
            "vendor_name": {
              "anyOf": [
                {
                  "type": "string"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            },
            "strategy_name": {
              "anyOf": [
                {
                  "type": "string"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            },
            "variables": {
              "anyOf": [
                {
                  "additionalProperties": {
                    "type": "string"
                  },
                  "type": "object"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            },
            "attachments": {
              "anyOf": [
                {
                  "items": {
                    "type": "string"
                  },
                  "type": "array"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            },
            "temperature": {
              "anyOf": [
                {
                  "type": "number"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            },
            "top_p": {
              "anyOf": [
                {
                  "type": "number"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            },
            "presence_penalty": {
              "anyOf": [
                {
                  "type": "number"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            },
            "frequency_penalty": {
              "anyOf": [
                {
                  "type": "number"
                },
                {
                  "type": "null"
                }
              ],
              "default": null
            }
          },
          "type": "object"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional configuration for execution parameters."
    },
    "model_name": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional model name override (e.g., \"gpt-4\", \"claude-3-opus\")."
    },
    "vendor_name": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional vendor name override (e.g., \"openai\", \"anthropic\")."
    },
    "temperature": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional temperature for LLM (0.0-2.0, controls randomness)."
    },
    "top_p": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional top-p for LLM (0.0-1.0, nucleus sampling)."
    },
    "presence_penalty": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional presence penalty (-2.0-2.0, reduces repetition)."
    },
    "frequency_penalty": {
      "anyOf": [
        {
          "type": "number"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional frequency penalty (-2.0-2.0, reduces frequency)."
    },
    "strategy_name": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional strategy name for pattern execution."
    },
    "variables": {
      "anyOf": [
        {
          "additionalProperties": {
            "type": "string"
          },
          "type": "object"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional map of key-value strings for pattern variables."
    },
    "attachments": {
      "anyOf": [
        {
          "items": {
            "type": "string"
          },
          "type": "array"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "Optional list of file paths/URLs to attach to the pattern."
    }
  },
  "required": [
    "pattern_name"
  ],
  "type": "object"
}
Output schema
{
  "properties": {
    "result": {
      "anyOf": [
        {
          "additionalProperties": true,
          "type": "object"
        },
        {
          "items": {
            "additionalProperties": true,
            "type": "object"
          },
          "type": "array"
        }
      ]
    }
  },
  "required": [
    "result"
  ],
  "type": "object",
  "x-fastmcp-wrap-result": true
}
——

Resources 0

  • None observed.

Resource templates 0

  • None observed.

Prompts 0

  • None observed.

Remote endpoints

EndpointTransportAuthenticationHealthObserved
No verified remote endpoint is linked.

Fabric MCP Server questions

How do I install Fabric MCP Server?

Install the selected package version with: python -m pip install 'fabric-mcp==1.2.1'

What tools does Fabric MCP Server provide?

Fabric MCP Server exposed 6 tools during independent protocol observation, including fabric_get_configuration, fabric_get_pattern_details, fabric_list_models, fabric_list_patterns, fabric_list_strategies, fabric_run_pattern.

Is Fabric MCP Server secure?

The selected current version does not yet have completed public verification. Unknown does not mean clean or vulnerable.

Company and product intelligence

These internal links are derived from strong identity fields such as the implementation name, package, repository, vendor, and listing name—not generic description prose.

Associated company landscape

Microsoft & Azure intelligence →

Association is based on retained identity fields; it does not by itself prove first-party publication.

Microsoft Fabric 63 matches

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