# ManagePrompt

According to OpenAITools.app telemetry verified on 2026-11-11, ManagePrompt (manageprompt.com) is an AI platform indexed under AI Developer Tools generating 233 monthly visits with a month-over-month traffic delta of +233 (0%). Its primary geographic market is Italy (100% traffic share), and it operates on a Open Source, Free pricing model. Top competing alternatives by monthly volume include Ollama (9.42M visits/mo), PromptLayer (85.9K visits/mo), Maxim AI (121.35K visits/mo).

Capture and inspect every LLM API call from a local web UI

## Key Telemetry & Specifications

| Metric | Value |
| :--- | :--- |
| Tool Name | ManagePrompt |
| Handle | manageprompt |
| Status | active |
| Origin | open_source |
| Maintenance | active |
| Official Domain | manageprompt.com |
| Website URL | https://manageprompt.com |
| Categories | AI Developer Tools, AI API, AI Workflow, Prompt Engineering |
| Pricing Model | Open Source, Free |
| Monthly Visits | 233 |
| MoM Traffic Change | 233 |
| MoM Growth Rate | 0% |
| Primary Market | Italy |
| Market Share | 100% |
| Direct Visits | 92 |
| Organic Search Visits | 0 |
| Social Visits | 0 |
| Referral Visits | 27 |
| Email Visits | 6 |
| Review Score | 4.4 |
| Saved Count | 0 |
| Supported Platforms | Website |
| Billing Platforms |  |
| Attributes | Features: Website; Pricing: Contact for Pricing |
| Tags | AI development, AI deployment, Prompt engineering, Model management, API integration, AI security, Rate limiting, Caching, Authentication, Analytics |

## Overview

Debugging an LLM-backed feature is awkward because the interesting part — the exact prompt that was sent and the raw response that came back — is usually invisible. ManagePrompt closes that gap with a small local capture layer. You add a line or two to your application, every completion call gets recorded, and a local web UI shows the request and response bodies, token counts, estimated cost and latency as the calls happen.

Integration is deliberately minimal. TypeScript and JavaScript projects can wrap their model with an AI SDK middleware, while code using the OpenAI SDK can pass requests through a capture() wrapper. Under the hood it works with any provider — OpenAI, Anthropic, Google, Mistral and others — and captures streaming and non-streaming calls alike, so you do not lose visibility on the calls that are hardest to inspect.

Everything runs locally and is stored in a project-scoped SQLite database, which means no hosted account and no prompts leaving your machine. The server component, which serves the web UI, is distributed through Homebrew and Go, while the capture package ships on npm. The project is MIT licensed and developed in the open.

## Pricing & Plans

Free and open source under the MIT licence. There is no hosted subscription: you install the local server via Homebrew or Go and add the npm capture package to your app. The only costs are those charged by the model providers you call, which the UI estimates using models.dev pricing data.

## Key Features & Capabilities

- **Full request and response capture:** Every LLM call made during development is recorded with both the request and response bodies, plus a visual flow view so you can follow the conversation structure at a glance.
- **Token and cost tracking:** Input, output, cache-read and cache-write tokens are counted for each call, with cost estimated in real time using models.dev pricing data.
- **Live local UI:** A WebSocket-powered interface updates as calls happen, so you can watch a run unfold rather than digging through log files after the fact.
- **Streaming-aware capture:** Streaming and non-streaming calls are both captured automatically, with no need to change how your application calls the model.
- **Zero-config local storage:** Each project directory gets its own SQLite database, so captured calls are isolated per project and nothing leaves your machine.

## Primary Use Cases

- **Debugging prompts during development (AI application developer):** Wrap your model in development and see the exact prompt and full response for each call, along with token counts, so a misbehaving prompt is diagnosed in minutes instead of by guesswork.
- **Cost and token auditing (Engineering lead):** Watch input, output and cache token counts per call with real-time cost estimates to find the prompts and context blobs that are quietly inflating your bill.
- **Verifying multi-step agent behaviour (Agent builder):** Use the flow visualisation to confirm how a multi-step agent chains its model calls and where a tool result or system message gets dropped.
- **Evaluating model and prompt changes (Product engineer):** Compare latency and token usage between models or prompt variants directly in the local UI while you iterate, without wiring up separate instrumentation.

## Strengths

- Runs entirely locally with a project-scoped SQLite database, so prompts and responses never leave your machine
- Cost and latency estimates are computed per call, making expensive prompts obvious before they reach production
- Setup is two lines for both the AI SDK middleware and the OpenAI SDK capture wrapper
- MIT licensed and developed in the open, so you can inspect and adapt the code

## Limitations

- Aimed at local development rather than production monitoring or team-wide observability
- You need to install and run a server component yourself, which adds a step to onboarding
- There is no hosted dashboard, so sharing a captured session with a teammate is not built in

## Frequently Asked Questions

### Is ManagePrompt free?
The project is published as open source under the MIT licence and is installed and run locally, so there is no hosted subscription to pay for. You only pay whatever third-party models you call.

### Where is my data stored?
In a SQLite database scoped to your project directory on your own machine. Captured requests and responses stay local and are surfaced through the local web UI.

### Which providers and SDKs are supported?
It works with any LLM API — OpenAI, Anthropic, Google, Mistral and others. For TypeScript and JavaScript apps there is an AI SDK middleware, and for the OpenAI SDK there is a capture() wrapper; two lines of setup either way.

### Does it handle streaming responses?
Yes. Both streaming and non-streaming calls are captured automatically, with the web UI updating live over WebSocket as calls happen.

### What is ManagePrompt's monthly traffic and growth trend?
ManagePrompt currently receives 233 monthly visits, with a month-over-month traffic change of +233 (0% growth rate). Its primary source market is Italy (100% share), including 92 direct visits/mo and 0 organic search visits/mo.

### Is ManagePrompt free? What is its pricing model?
ManagePrompt operates on a Open Source, Free pricing model. Free and open source under the MIT licence. There is no hosted subscription: you install the local server via Homebrew or Go and add the npm capture package to your app. The only costs are those charged by the model providers you call, which the UI estimates using models.dev pricing data. Supported billing and checkout platforms include: not listed.

### What are the best ManagePrompt alternatives in 2026?
Based on OpenAITools.app category traffic and feature fit, the top five alternatives to ManagePrompt are: 1. Ollama (9.42M visits/mo); 2. PromptLayer (85.9K visits/mo); 3. Maxim AI (121.35K visits/mo); 4. Weights & Biases (CoreWeave Forge) (315.62K visits/mo); 5. Tokenomy.ai (5.32K visits/mo).

### Which platforms and core AI capabilities does ManagePrompt support?
ManagePrompt is classified under AI Developer Tools, AI API, AI Workflow, Prompt Engineering, supports the following platforms: Website, and its core capability tags include: AI development, AI deployment, Prompt engineering, Model management, API integration, AI security.

## Alternatives

| Tool Name | Monthly Visits | Pricing Model | Compare |
| :--- | :--- | :--- | :--- |
| [Ollama](https://openaitools.app/tool/ollama) | 9,421,973 | Free, Freemium, Paid | [Compare](https://openaitools.app/compare/manageprompt-vs-ollama) |
| [PromptLayer](https://openaitools.app/tool/promptlayer) | 85,899 | Free Trial, Contact for Pricing | [Compare](https://openaitools.app/compare/manageprompt-vs-promptlayer) |
| [Maxim AI](https://openaitools.app/tool/maxim-ai) | 121,351 | Contact for Pricing, Free Open Source | [Compare](https://openaitools.app/compare/manageprompt-vs-maxim-ai) |
| [Weights & Biases (CoreWeave Forge)](https://openaitools.app/tool/prompts) | 315,624 | Freemium, Contact for Pricing, Free | [Compare](https://openaitools.app/compare/manageprompt-vs-prompts) |
| [Tokenomy.ai](https://openaitools.app/tool/tokenomy-ai) | 5,320 | Freemium | [Compare](https://openaitools.app/compare/manageprompt-vs-tokenomy-ai) |
| [Caveman](https://openaitools.app/tool/caveman) | 171,826 | Freemium, Contact for Pricing | [Compare](https://openaitools.app/compare/caveman-vs-manageprompt) |
| [Open WebUI](https://openaitools.app/tool/open-webui) | 804,534 | Freemium | [Compare](https://openaitools.app/compare/manageprompt-vs-open-webui) |
| [Latitude](https://openaitools.app/tool/latitude) | 48,210 | Freemium, Open Source, Enterprise | [Compare](https://openaitools.app/compare/latitude-vs-manageprompt) |
| [Arize AI](https://openaitools.app/tool/arize-com) | 249,028 | Paid, Contact for Pricing | [Compare](https://openaitools.app/compare/arize-com-vs-manageprompt) |
| [honeyhive.ai](https://openaitools.app/tool/honeyhive-ai) | 8,835 | Freemium, Contact for Pricing | [Compare](https://openaitools.app/compare/honeyhive-ai-vs-manageprompt) |
| [Vellum](https://openaitools.app/tool/vellum) | 331,901 | Freemium, Paid | [Compare](https://openaitools.app/compare/manageprompt-vs-vellum) |
| [Confident AI](https://openaitools.app/tool/confident-ai) | 83,400 | Freemium, Paid, Contact for Pricing | [Compare](https://openaitools.app/compare/confident-ai-vs-manageprompt) |

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Source: https://openaitools.app/tool/manageprompt