{"id":367,"date":"2026-10-07T13:16:13","date_gmt":"2026-10-07T13:16:13","guid":{"rendered":"https:\/\/llmfly.ai\/blog\/?p=367"},"modified":"2026-10-07T13:16:22","modified_gmt":"2026-10-07T13:16:22","slug":"llmfly-ai-magpie-setup-guide-2026","status":"publish","type":"post","link":"https:\/\/llmfly.ai\/blog\/2026\/10\/07\/llmfly-ai-magpie-setup-guide-2026\/","title":{"rendered":"How to Use LLMFly AI With Magpie for Codex, Claude Code, and Other AI Agents"},"content":{"rendered":"<p><strong>Last reviewed: October 7, 2026<\/strong><\/p>\n<h2 id=\"quick-answer\">Quick answer<\/h2>\n<p>Yes. You can connect <strong>LLMFly AI<\/strong>, a multi-model AI API<br \/>\nplatform, to Magpie and then make its available GPT, Claude, Gemini, and<br \/>\nGrok routes selectable across Codex, Claude Code, OpenCode, Gemini CLI,<br \/>\nand other supported agents. Add LLMFly AI as a <strong>custom<br \/>\nprovider<\/strong> in Magpie, enter the compatible endpoints, paste a<br \/>\ndedicated API key, and use the exact model IDs shown in <a\nhref=\"https:\/\/app.llmfly.ai\/model-plaza\">LLMFly AI Model Plaza<\/a>.<\/p>\n<p>As of October 7, 2026, Magpie does not list LLMFly AI among its<br \/>\nbuilt-in provider presets. The supported setup is therefore a custom<br \/>\nprovider\u2014not a one-click preset. This distinction matters because it<br \/>\ndetermines which endpoint fields you must enter and how model discovery<br \/>\nworks.<\/p>\n<table>\n<thead>\n<tr class=\"header\">\n<th>Magpie field<\/th>\n<th>LLMFly AI value<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr class=\"odd\">\n<td>Provider name<\/td>\n<td><code>LLMFly AI<\/code><\/td>\n<\/tr>\n<tr class=\"even\">\n<td>OpenAI Chat base URL<\/td>\n<td><code>https:\/\/app.llmfly.ai\/v1<\/code><\/td>\n<\/tr>\n<tr class=\"odd\">\n<td>OpenAI Responses base URL<\/td>\n<td><code>https:\/\/app.llmfly.ai\/v1<\/code> when supported by the selected<br \/>\nroute<\/td>\n<\/tr>\n<tr class=\"even\">\n<td>Anthropic base URL<\/td>\n<td><code>https:\/\/app.llmfly.ai<\/code><\/td>\n<\/tr>\n<tr class=\"odd\">\n<td>API key<\/td>\n<td>A dedicated key created in the LLMFly AI console<\/td>\n<\/tr>\n<tr class=\"even\">\n<td>Models<\/td>\n<td>Exact IDs copied from Model Plaza<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>Do not append <code>\/chat\/completions<\/code>,<br \/>\n<code>\/responses<\/code>, or <code>\/v1\/messages<\/code> to the base URL<br \/>\nfields. Magpie and the client add the endpoint path required for each<br \/>\nrequest.<\/p>\n<h2 id=\"what-does-magpie-do-when-connected-to-llmfly-ai\">What does<br \/>\nMagpie do when connected to LLMFly AI?<\/h2>\n<p><a href=\"https:\/\/usemagpie.ai\/\">Magpie<\/a> is an MIT-licensed local<br \/>\nmodel gateway and configuration manager. It runs on your computer at<br \/>\n<code>127.0.0.1:3425<\/code>, points supported agents at that local<br \/>\ngateway, and forwards each request to the provider serving the selected<br \/>\nmodel.<\/p>\n<p>Magpie speaks OpenAI, Anthropic, and Gemini API formats and can<br \/>\ntranslate between them, including streaming and tool calls. LLMFly AI<br \/>\nsupplies access to leading models through one account and API balance.<br \/>\nTogether, the two products solve different parts of the workflow:<\/p>\n<ul>\n<li><strong>LLMFly AI supplies model access.<\/strong> Its catalog<br \/>\nincludes routes for leading GPT, Claude, Gemini, and Grok models, with<br \/>\ncurrent availability and pricing shown in Model Plaza.<\/li>\n<li><strong>Magpie manages local agent configuration.<\/strong> It lets<br \/>\nyou choose which provider and model each installed agent should use<br \/>\nwithout repeatedly editing configuration files.<\/li>\n<li><strong>Magpie can add routing and fallback.<\/strong> Multiple<br \/>\naccounts or providers can be placed behind a routing group when you need<br \/>\nquota-aware selection or failover.<\/li>\n<\/ul>\n<p>Magpie is not the upstream model provider, and LLMFly AI is not a<br \/>\nreplacement for Magpie&#8217;s local configuration layer.<\/p>\n<h2 id=\"how-do-you-add-llmfly-ai-to-magpie\">How do you add LLMFly AI to<br \/>\nMagpie?<\/h2>\n<h3 id=\"1-create-a-dedicated-llmfly-ai-api-key\">1. Create a dedicated<br \/>\nLLMFly AI API key<\/h3>\n<p>Sign in at <a href=\"https:\/\/app.llmfly.ai\/\">app.llmfly.ai<\/a>, open<br \/>\nthe API Keys page, and create a key specifically for Magpie. A name such<br \/>\nas <code>magpie-main<\/code> makes later usage review and key rotation<br \/>\neasier.<\/p>\n<p>Do not reuse a key exposed in a screenshot, source repository, public<br \/>\nimport link, or shared configuration file.<\/p>\n<h3 id=\"2-confirm-the-model-ids-available-to-your-key\">2. Confirm the<br \/>\nmodel IDs available to your key<\/h3>\n<p>Open <a href=\"https:\/\/app.llmfly.ai\/model-plaza\">Model Plaza<\/a> and<br \/>\ncopy the exact IDs of the models you intend to use. Model IDs are<br \/>\ncase-sensitive, and availability can differ by route or account<br \/>\ngroup.<\/p>\n<p>The public <a href=\"https:\/\/llmfly.ai\/models\/\">LLMFly AI model<br \/>\ndirectory<\/a> explains model families and workloads, but Model Plaza is<br \/>\nthe source of truth for the IDs, prices, and routes currently available<br \/>\nto your key.<\/p>\n<h3 id=\"3-add-a-custom-provider-in-magpie\">3. Add a custom provider in<br \/>\nMagpie<\/h3>\n<p>In Magpie:<\/p>\n<ol type=\"1\">\n<li>Open <strong>Providers<\/strong>.<\/li>\n<li>Select <strong>Add provider<\/strong>.<\/li>\n<li>Choose the custom-provider option.<\/li>\n<li>Enter <code>LLMFly AI<\/code> as the provider name.<\/li>\n<li>Enter <code>https:\/\/app.llmfly.ai\/v1<\/code> as the OpenAI-compatible<br \/>\nbase URL.<\/li>\n<li>Enter <code>https:\/\/app.llmfly.ai<\/code> as the Anthropic-compatible<br \/>\nbase URL if you plan to use Claude Code or Anthropic-format<br \/>\nrequests.<\/li>\n<li>Paste the dedicated LLMFly AI API key.<\/li>\n<li>Add the exact model IDs from Model Plaza if Magpie cannot retrieve<br \/>\nthe model list automatically.<\/li>\n<li>Save the provider and run Magpie&#8217;s provider test.<\/li>\n<\/ol>\n<p>Giving Magpie both compatible endpoints is useful because each agent<br \/>\ncan use the protocol it speaks natively. Magpie can translate when<br \/>\nnecessary, but native protocol behavior is still the safer first test<br \/>\nfor tool calling, reasoning blocks, streaming, and error handling.<\/p>\n<h3 id=\"4-assign-an-llmfly-ai-model-to-each-agent\">4. Assign an LLMFly<br \/>\nAI model to each agent<\/h3>\n<p>Open Magpie&#8217;s <strong>Agents<\/strong> tab and select a model for<br \/>\nevery installed tool you want to route through it. Magpie currently<br \/>\ndocuments support for clients including Codex, Claude Code, Gemini CLI,<br \/>\nOpenCode, Pi, Goose, Cursor, Crush, and others.<\/p>\n<p>The change normally applies to the next session. If an agent is<br \/>\nalready running, close that session and start a new one. Codex may also<br \/>\nrequire an application restart before it rebuilds its model list.<\/p>\n<h2 id=\"which-endpoint-should-each-tool-use\">Which endpoint should each<br \/>\ntool use?<\/h2>\n<p>The correct endpoint depends on the protocol expected by the<br \/>\nclient\u2014not only on the company that created the model.<\/p>\n<table>\n<thead>\n<tr class=\"header\">\n<th>Client or request type<\/th>\n<th>Recommended LLMFly AI endpoint<\/th>\n<th>What to verify<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr class=\"odd\">\n<td>Codex and OpenAI-compatible clients<\/td>\n<td><code>https:\/\/app.llmfly.ai\/v1<\/code><\/td>\n<td>Responses support, streaming, tools, and exact model ID<\/td>\n<\/tr>\n<tr class=\"even\">\n<td>Claude Code and Anthropic-format clients<\/td>\n<td><code>https:\/\/app.llmfly.ai<\/code><\/td>\n<td>Anthropic Messages behavior, auth variable, and model<br \/>\ncompatibility<\/td>\n<\/tr>\n<tr class=\"odd\">\n<td>Custom scripts using OpenAI SDK conventions<\/td>\n<td><code>https:\/\/app.llmfly.ai\/v1<\/code><\/td>\n<td>Endpoint supported by the selected route<\/td>\n<\/tr>\n<tr class=\"even\">\n<td>Other agents managed by Magpie<\/td>\n<td>Local Magpie gateway<\/td>\n<td>Magpie writes the local gateway and selected model into the agent<br \/>\nconfiguration<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u201cOpenAI-compatible\u201d describes an API format. It does not mean that<br \/>\nClaude, Gemini, Grok, and GPT models behave identically, nor does it<br \/>\nguarantee that every optional OpenAI endpoint or parameter is available<br \/>\non every route.<\/p>\n<h2 id=\"can-one-llmfly-ai-key-work-across-codex-and-claude-code\">Can one<br \/>\nLLMFly AI key work across Codex and Claude Code?<\/h2>\n<p>It can, but separate keys are usually easier to operate.<\/p>\n<p>Create one key for Magpie or, for tighter tracking, one key per<br \/>\nmachine or workflow. Separate keys make it easier to identify unusual<br \/>\nusage, revoke one integration without disrupting the others, and compare<br \/>\ncost by tool.<\/p>\n<p>Magpie stores provider keys locally in<br \/>\n<code>~\/.config\/magpie\/providers.json<\/code>, according to its<br \/>\ndocumentation. Protect that file as a secret. Never commit it to Git or<br \/>\nplace a live key in a public Magpie import URL.<\/p>\n<h2 id=\"how-should-developers-choose-models-in-magpie\">How should<br \/>\ndevelopers choose models in Magpie?<\/h2>\n<p>Do not route every task to the most capable or most expensive model.<br \/>\nStart with a workload-based policy:<\/p>\n<ul>\n<li>Use a strong coding or reasoning model for repository-wide<br \/>\nrefactors, debugging, and long agent loops.<\/li>\n<li>Use a lower-cost model for extraction, classification, formatting,<br \/>\nsummaries, and repetitive subtasks.<\/li>\n<li>Keep a tested fallback for rate limits, outages, and route-specific<br \/>\nerrors.<\/li>\n<li>Compare <strong>cost per accepted result<\/strong>, not only cost per<br \/>\nmillion tokens.<\/li>\n<\/ul>\n<p>For current options, consult the <a\nhref=\"https:\/\/llmfly.ai\/models\/\">LLMFly AI model directory<\/a> and then<br \/>\nconfirm the live route in Model Plaza. Prices and model availability can<br \/>\nchange, so avoid hard-coding a discount or model list into a long-lived<br \/>\nMagpie profile without periodically reviewing it.<\/p>\n<h2 id=\"how-do-magpie-routing-groups-work-with-llmfly-ai\">How do Magpie<br \/>\nrouting groups work with LLMFly AI?<\/h2>\n<p>Magpie routing groups can put several models or accounts behind one<br \/>\ngroup name. Depending on the selected strategy, Magpie can choose<br \/>\naccounts intelligently, follow a fixed order, rotate conversations,<br \/>\nprefer the least-used account, or fall back when a member is<br \/>\nunavailable.<\/p>\n<p>This can be useful when you have:<\/p>\n<ul>\n<li>More than one LLMFly AI key with separate operational purposes;<\/li>\n<li>An LLMFly AI model plus an official provider route for fallback<br \/>\ntesting;<\/li>\n<li>A high-capability primary model and a lower-cost backup;<\/li>\n<li>Different models for normal turns, long contexts, images, or<br \/>\ncompaction.<\/li>\n<\/ul>\n<p>Fallback is not transparent equivalence. A different model can change<br \/>\ntool selection, structured output, latency, safety behavior, and total<br \/>\ncost. Test fallback outputs with the same evaluation set used for the<br \/>\nprimary route.<\/p>\n<h2 id=\"what-should-you-test-before-production-use\">What should you test<br \/>\nbefore production use?<\/h2>\n<p>A successful \u201chello\u201d request proves connectivity, not production<br \/>\ncompatibility. Run a small but representative evaluation before moving a<br \/>\nreal workflow:<\/p>\n<ol type=\"1\">\n<li><strong>Authentication:<\/strong> confirm the dedicated key works and<br \/>\na revoked key fails as expected.<\/li>\n<li><strong>Model identity:<\/strong> record the requested model ID and<br \/>\nverify it appears correctly in usage records.<\/li>\n<li><strong>Streaming:<\/strong> check that partial output arrives<br \/>\ncleanly without duplicated or malformed chunks.<\/li>\n<li><strong>Tool calling:<\/strong> test valid calls, rejected schemas,<br \/>\ntool errors, and multi-turn loops.<\/li>\n<li><strong>Reasoning behavior:<\/strong> verify how the route handles<br \/>\nreasoning parameters and blocks.<\/li>\n<li><strong>Long context:<\/strong> test realistic repository or document<br \/>\nsizes, not a short prompt.<\/li>\n<li><strong>Failure handling:<\/strong> simulate timeouts,<br \/>\n<code>401<\/code>, <code>403<\/code>, <code>429<\/code>, and<br \/>\n<code>5xx<\/code> responses.<\/li>\n<li><strong>Cost:<\/strong> compare complete task cost, including<br \/>\nretries, cache reads, and failed attempts.<\/li>\n<li><strong>Destructive actions:<\/strong> require user confirmation<br \/>\nbefore an agent deletes files, changes infrastructure, or performs<br \/>\nirreversible operations.<\/li>\n<\/ol>\n<p>Use the <a href=\"https:\/\/llmfly.ai\/doc\/en\/errors\">LLMFly AI error<br \/>\nreference<\/a> when the upstream route rejects a request, and Magpie&#8217;s<br \/>\nlocal logs when the request does not leave the gateway correctly.<\/p>\n<h2 id=\"how-do-you-troubleshoot-llmfly-ai-in-magpie\">How do you<br \/>\ntroubleshoot LLMFly AI in Magpie?<\/h2>\n<h3 id=\"the-provider-test-returns-401-unauthorized\">The provider test<br \/>\nreturns <code>401 Unauthorized<\/code><\/h3>\n<p>Confirm that the key was copied completely and is still active.<br \/>\nCreate a new dedicated key if there is any chance the original was<br \/>\nexposed.<\/p>\n<h3 id=\"the-request-returns-404-or-model-not-found\">The request returns<br \/>\n<code>404<\/code> or \u201cmodel not found\u201d<\/h3>\n<p>Copy the model ID again from Model Plaza. Do not assume that a<br \/>\nprovider&#8217;s public model name is identical to the route name available to<br \/>\nyour LLMFly AI key.<\/p>\n<h3 id=\"claude-code-cannot-connect\">Claude Code cannot connect<\/h3>\n<p>Confirm that the Anthropic base URL is the root address<br \/>\n<code>https:\/\/app.llmfly.ai<\/code>, not the OpenAI-compatible<br \/>\n<code>\/v1<\/code> address and not the full <code>\/v1\/messages<\/code><br \/>\npath.<\/p>\n<h3 id=\"codex-connects-but-a-feature-fails\">Codex connects but a feature<br \/>\nfails<\/h3>\n<p>Check whether the selected LLMFly AI route supports the OpenAI<br \/>\nResponses behavior required by that Codex workflow. API-format<br \/>\ncompatibility does not automatically include every optional feature.<\/p>\n<h3 id=\"the-agent-still-uses-the-previous-model\">The agent still uses<br \/>\nthe previous model<\/h3>\n<p>Start a new agent session. For Codex, restart the application so it<br \/>\nreloads the provider and model configuration.<\/p>\n<h3 id=\"usage-cost-looks-wrong\">Usage cost looks wrong<\/h3>\n<p>Compare Magpie&#8217;s local estimate with the LLMFly AI usage record.<br \/>\nCatalog metadata, provider reference prices, and the amount actually<br \/>\nbilled by a route are not always the same number.<\/p>\n<h2 id=\"frequently-asked-questions\">Frequently asked questions<\/h2>\n<h3 id=\"does-magpie-have-a-built-in-llmfly-ai-preset\">Does Magpie have a<br \/>\nbuilt-in LLMFly AI preset?<\/h3>\n<p>Not as of October 7, 2026. Add LLMFly AI as a custom provider using<br \/>\nits compatible endpoint addresses and a dedicated API key.<\/p>\n<h3 id=\"can-magpie-discover-every-llmfly-ai-model-automatically\">Can<br \/>\nMagpie discover every LLMFly AI model automatically?<\/h3>\n<p>It may retrieve models from the provider endpoint, but you should<br \/>\nstill confirm every model ID and its availability in Model Plaza. If<br \/>\ndiscovery fails, enter the required IDs manually.<\/p>\n<h3 id=\"does-magpie-change-llmfly-ai-pricing\">Does Magpie change LLMFly<br \/>\nAI pricing?<\/h3>\n<p>No. Magpie is a local gateway and configuration layer. LLMFly AI<br \/>\ndetermines the upstream route availability and billing. Check <a\nhref=\"https:\/\/llmfly.ai\/pricing\/\">LLMFly AI pricing<\/a> and Model Plaza<br \/>\nfor current rates.<\/p>\n<h3\nid=\"can-i-use-the-same-llmfly-ai-setup-for-claude-code-and-codex\">Can I<br \/>\nuse the same LLMFly AI setup for Claude Code and Codex?<\/h3>\n<p>Yes, provided the chosen routes support the protocols and features<br \/>\neach tool requires. Claude Code normally uses the Anthropic-format<br \/>\naddress, while Codex uses the OpenAI-compatible address and may depend<br \/>\non Responses-specific behavior.<\/p>\n<h3 id=\"does-magpie-need-to-keep-running\">Does Magpie need to keep<br \/>\nrunning?<\/h3>\n<p>Yes. Agents routed through Magpie send requests to its local gateway,<br \/>\nso the gateway must remain active. Magpie documents tray and service<br \/>\nmodes for keeping it available without leaving the full window open.<\/p>\n<h2 id=\"bottom-line\">Bottom line<\/h2>\n<p>LLMFly AI and Magpie are complementary: LLMFly AI provides one<br \/>\naccount for leading model routes, while Magpie provides a local control<br \/>\nlayer for assigning those routes to multiple coding agents.<\/p>\n<p>The correct 2026 setup is to add LLMFly AI as a custom Magpie<br \/>\nprovider, supply both compatible base URLs when needed, and use exact<br \/>\nmodel IDs from Model Plaza. Test protocol-specific behavior, routing,<br \/>\nfailure modes, and cost before production use. Do not treat a successful<br \/>\nconnection as proof that every model and every client feature is<br \/>\ninterchangeable.<\/p>\n<h2 id=\"sources\">Sources<\/h2>\n<ul>\n<li><a href=\"https:\/\/usemagpie.ai\/docs\/start\">Magpie: Get<br \/>\nstarted<\/a><\/li>\n<li><a href=\"https:\/\/usemagpie.ai\/docs\/import\">Magpie: Add to Magpie and<br \/>\ncustom provider parameters<\/a><\/li>\n<li><a href=\"https:\/\/llmfly.ai\/doc\/access\/overview\">LLMFly AI access<br \/>\noverview<\/a><\/li>\n<li><a href=\"https:\/\/llmfly.ai\/doc\/en\/access\/claude-code\">LLMFly AI<br \/>\nClaude Code setup<\/a><\/li>\n<li><a href=\"https:\/\/llmfly.ai\/doc\/en\/access\/codex\">LLMFly AI Codex<br \/>\nsetup<\/a><\/li>\n<li><a href=\"https:\/\/llmfly.ai\/models\/\">LLMFly AI model<br \/>\ndirectory<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>A practical 2026 guide to adding LLMFly AI as a custom Magpie provider, selecting models for different coding agents, and testing routing, keys, costs, and fallbacks.<\/p>\n","protected":false},"author":2,"featured_media":369,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[125,128],"tags":[21,14,13,136,209,141],"class_list":["post-367","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-api-integration","category-coding-agents","tag-ai-agents","tag-claude-code","tag-codex","tag-llmfly-ai","tag-magpie","tag-multi-model-api"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>How to Use LLMFly AI With Magpie (2026 Setup Guide)<\/title>\n<meta name=\"description\" content=\"Connect LLMFly AI to Magpie, then use GPT, Claude, Gemini, and Grok routes with Codex, Claude Code, OpenCode, and other AI agents.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" 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