|
| 1 | +# Integrations content |
| 2 | +--- |
| 3 | +integrations: |
| 4 | + # Template (do not remove) |
| 5 | + # |
| 6 | + # - name: "Mandatory Short Name of the Service or Application (plain text)" |
| 7 | + # icon: "icon spec - have a look at https://squidfunk.github.io/mkdocs-material/reference/icons-emojis/" |
| 8 | + # content: | |
| 9 | + # Mandatory small markdown paragraph which describes, what you can do with the service or application. |
| 10 | + # The content should have at least one link. |
| 11 | + # Possible placeholders: |
| 12 | + # - {{p.pluginID}} - markdownlink to plugin (replace all '-' with '_') |
| 13 | + # - {{p.pluginID_ref}} - relative link to plugin (replace all '-' with '_') |
| 14 | + |
| 15 | + ##### |
| 16 | + # LLM Provider |
| 17 | + ##### |
| 18 | + |
| 19 | + - name: Ollama |
| 20 | + icon: ":simple-ollama:" |
| 21 | + content: | |
| 22 | + Use the {{p.cmem_plugin_llm_ExecuteInstructions}} or {{p.cmem_plugin_llm_CreateEmbeddings}} task |
| 23 | + to interact with Ollama provided Large Language Models (LLMs). |
| 24 | +
|
| 25 | + - name: Azure AI Foundry |
| 26 | + icon: ":material-microsoft-azure:" |
| 27 | + content: | |
| 28 | + Use the {{p.cmem_plugin_llm_ExecuteInstructions}} or {{p.cmem_plugin_llm_CreateEmbeddings}} task |
| 29 | + to interact with Azure AI Foundry provided Large Language Models (LLMs). |
| 30 | +
|
| 31 | + - name: OpenRouter |
| 32 | + icon: ":octicons-ai-model-24:" |
| 33 | + content: | |
| 34 | + Use the {{p.cmem_plugin_llm_ExecuteInstructions}} or {{p.cmem_plugin_llm_CreateEmbeddings}} task |
| 35 | + to interact with Anthropic / Claude provided Large Language Models (LLMs). |
| 36 | +
|
| 37 | + - name: Anthropic / Claude |
| 38 | + icon: ":simple-anthropic:" |
| 39 | + content: | |
| 40 | + Use the {{p.cmem_plugin_llm_ExecuteInstructions}} or {{p.cmem_plugin_llm_CreateEmbeddings}} task |
| 41 | + to interact with Anthropic / Claude provided Large Language Models (LLMs). |
| 42 | +
|
| 43 | + - name: OpenAI |
| 44 | + icon: ":simple-openai:" |
| 45 | + content: | |
| 46 | + Use the {{p.cmem_plugin_llm_ExecuteInstructions}} or {{p.cmem_plugin_llm_CreateEmbeddings}} task |
| 47 | + to interact with OpenAI provided Large Language Models (LLMs). |
| 48 | +
|
| 49 | +
|
| 50 | + ##### |
| 51 | + # Services |
| 52 | + ##### |
| 53 | + |
| 54 | + - name: Office 365 |
| 55 | + icon: ":material-microsoft-office:" |
| 56 | + content: | |
| 57 | + Use the {{p.office365preadsheet}} to read and write to Excel workbooks in Office 365. |
| 58 | +
|
| 59 | + - name: Google Drive |
| 60 | + icon: ":material-google-drive:" |
| 61 | + content: | |
| 62 | + Use the {{p.googlespreadsheet}} to read and write to Excel workbooks in Google Drive. |
| 63 | +
|
| 64 | + - name: SSH |
| 65 | + icon: ":material-ssh:" |
| 66 | + content: | |
| 67 | + Interact with SSH servers to {{p.cmem_plugin_ssh_Download}} or {{p.cmem_plugin_ssh_Execute}}. |
| 68 | +
|
| 69 | + - name: Kubernetes |
| 70 | + icon: ":simple-kubernetes:" |
| 71 | + content: | |
| 72 | + You can {{p.cmem_plugin_kubernetes_Execute}} and captures its output to process it. |
| 73 | +
|
| 74 | + - name: GraphQL |
| 75 | + icon: ":simple-graphql:" |
| 76 | + content: | |
| 77 | + You can execute a {{p.cmem_plugin_graphql_workflow_graphql_GraphQLPlugin}} and process the result in a workflow. |
| 78 | +
|
| 79 | + - name: eMail / SMTP |
| 80 | + icon: ":material-email-outline:" |
| 81 | + content: | |
| 82 | + Send plain text or HTML formatted [eMail messages]({{p.SendEMail_ref}}) using an SMTP server. |
| 83 | +
|
| 84 | + - name: Jira |
| 85 | + icon: ":simple-jira:" |
| 86 | + content: | |
| 87 | + Execute a {{p.cmem_plugin_jira_JqlQuery}} on a Jira instance to fetch and integrate issue data. |
| 88 | +
|
| 89 | + - name: Kafka |
| 90 | + icon: ":simple-apachekafka:" |
| 91 | + content: | |
| 92 | + You can [send]({{p.cmem_plugin_kafka_SendMessages_ref}}) and |
| 93 | + [receive messages]({{p.cmem_plugin_kafka_ReceiveMessages_ref}}) to and from a Kafka topic. |
| 94 | +
|
| 95 | + - name: Nextcloud |
| 96 | + icon: ":simple-nextcloud:" |
| 97 | + content: | |
| 98 | + Use a Nextcloud instance to [download files]({{p.cmem_plugin_nextcloud_Download_ref}}) to process |
| 99 | + them or [upload files]({{p.cmem_plugin_nextcloud_Upload_ref}}) you created with Corporate Memory. |
| 100 | +
|
| 101 | + - name: Salesforce |
| 102 | + icon: ":fontawesome-brands-salesforce:" |
| 103 | + content: | |
| 104 | + Interact with your Salesforce data, such as {{p.cmem_plugin_salesforce_workflow_operations_SobjectCreate}} or |
| 105 | + execute a {{p.cmem_plugin_salesforce_SoqlQuery}}. |
| 106 | +
|
| 107 | + - name: Mattermost |
| 108 | + icon: ":simple-mattermost:" |
| 109 | + content: | |
| 110 | + Send workflow reports or any other message to user and groups in you Mattermost with |
| 111 | + the {{p.cmem_plugin_mattermost}} task. |
| 112 | +
|
| 113 | + ##### |
| 114 | + # Files |
| 115 | + ##### |
| 116 | + |
| 117 | + - name: YAML |
| 118 | + icon: ":simple-yaml:" |
| 119 | + content: | |
| 120 | + Load and integrate data from YAML files with the {{p.cmem_plugin_yaml_parse}} task. |
| 121 | +
|
| 122 | + - name: XML |
| 123 | + icon: ":material-xml:" |
| 124 | + content: | |
| 125 | + Load and write data to XML files with the {{p.xml}} dataset as well as |
| 126 | + {{p.XmlParserOperator}} from external services. |
| 127 | +
|
| 128 | + - name: CSV |
| 129 | + icon: ":fontawesome-solid-file-csv:" |
| 130 | + content: | |
| 131 | + Comma-separated values (CSV) is a text data format which can be processed |
| 132 | + (read and write) with the [CSV Dataset]({{p.csv_ref}}). |
| 133 | +
|
| 134 | + - name: Excel |
| 135 | + icon: ":fontawesome-solid-file-csv:" |
| 136 | + content: | |
| 137 | + Use the {{p.excel}} task to read and write to Excel workbooks in the Open XML format (XLSX). |
| 138 | +
|
| 139 | + - name: JSON |
| 140 | + icon: ":material-code-json:" |
| 141 | + content: | |
| 142 | + Use the {{p.json}} dataset to read and write JSON files (JavaScript Object Notation). |
| 143 | +
|
| 144 | + - name: Zipped JSON |
| 145 | + icon: ":material-code-json:" |
| 146 | + content: | |
| 147 | + Use the {{p.json}} dataset to read and write JSON files in a ZIP Archive. |
| 148 | +
|
| 149 | + - name: JSON Lines |
| 150 | + icon: ":material-code-json:" |
| 151 | + content: | |
| 152 | + Use the {{p.json}} dataset to read and write files in the [JSON Lines](https://jsonlines.org/) text file format. |
| 153 | +
|
| 154 | + ##### |
| 155 | + # Databases |
| 156 | + ##### |
| 157 | + |
| 158 | + - name: Neo4J |
| 159 | + icon: ":simple-neo4j:" |
| 160 | + content: | |
| 161 | + Use the {{p.neo4j}} dataset for reading and writing Neo4j graphs. |
| 162 | +
|
| 163 | + - name: PostgreSQL |
| 164 | + icon: ":simple-postgresql:" |
| 165 | + content: | |
| 166 | + PostgreSQL can be accessed with the {{p.Jdbc}} dataset and a proper JDBC driver. |
| 167 | +
|
| 168 | + - name: MariaDB |
| 169 | + icon: ":simple-mariadb:" |
| 170 | + content: | |
| 171 | + MariaDB can be accessed with the {{p.Jdbc}} dataset and a proper JDBC driver. |
| 172 | +
|
| 173 | + - name: SQLite |
| 174 | + icon: ":simple-sqlite:" |
| 175 | + content: | |
| 176 | + SQLite can be accessed with the {{p.Jdbc}} dataset and a proper JDBC driver. |
| 177 | +
|
| 178 | + - name: MySQL |
| 179 | + icon: ":simple-mysql:" |
| 180 | + content: | |
| 181 | + MySQL can be accessed with the {{p.Jdbc}} dataset and a proper JDBC driver. |
| 182 | +
|
| 183 | + - name: Microsoft SQL |
| 184 | + icon: ":material-microsoft:" |
| 185 | + content: | |
| 186 | + The Microsoft SQL Server can be accessed with the {{p.Jdbc}} dataset and a proper JDBC driver. |
| 187 | +
|
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