CoreStory Project Selections API
The project-selections API from CoreStory — 2 operation(s) for project-selections.
The project-selections API from CoreStory — 2 operation(s) for project-selections.
Every API here is available over the APIs.io API and to AI agents over MCP.
One button, every client — Claude, Cursor, VS Code and the rest.
https://apis.io/mcp
find_apisBrowse and filter every API in the catalog.get_api_artifactsOne API's artifacts, grouped by type.get_openapiThe primary OpenAPI for this API.find_similar_apisAPIs that look like this one.apis_io_searchSTART HERE — APIs, providers and tags for one query, each with its total.resolveTurn a domain, URL or GitHub org into the provider it belongs to.find_cohortsEvery scored population of providers in the catalog.curl "https://apis.io/api/v1/apis/corestory:corestory-project-selections-api"
curl "https://apis.io/api/v1/apis?limit=25"
Discovery needs no key. Ratings and market analysis are Pro.
Free tier, no form to fill in. Signing in shares your email address with us — we store it to create your key and to recognise you if you sign in with another provider. See our Privacy Policy and Terms.
A second provider on the same verified email joins the account you already have.
openapi: 3.2.0
info:
title: Crowdbotics API Documentation Project Selections API
description: '# CoreStory API Overview
The CoreStory API provides programmatic access to structured insights derived from software source code. It is designed for engineering, architecture, and product teams who need to extract business logic, technical specifications, architectural relationships, and system-level context from complex or legacy codebases. By interfacing directly with CoreStory API, users can:
- Generate full Product Requirements Documents (PRDs) from a codebase
- Extract detailed Technical Specifications for modernization or migration
- Query a codebase using natural language to surface implementation details, logic paths, dependencies, and architectural insights
- Construct and visualize knowledge graphs of systems, components, and relationships
- Ingest, store, and retrieve content from a vector store for AI-powered retrieval-augmented generation (RAG) workflows
CoreStory is especially valuable in contexts where:
- Codebases are large, unstructured, or under-documented
- Product and engineering teams are onboarding to unfamiliar systems
- Technical stakeholders require visibility into system design or feature coverage
- Modernization, replatforming, or M&A due diligence is underway
The API can be integrated into existing CI/CD pipelines, internal developer portals, architecture review boards, product planning processes, or documentation automation workflows. All endpoints support secure authentication and are designed for high-availability, asynchronous workloads. Output formats include JSON, Markdown, and PDF, with flexible formatting options for downstream consumption. For step-by-step usage instructions and workflows, refer to the CoreStory API Quick Start Guide. ## Features
* **Document Generation**
* Generate complete Product Requirements Documents (PRD)
* Generate Technical Specifications
* Generate individual document sections (executive overview, user personas, etc.)
* Format documents in JSON or Markdown
* **Vector Store Management**
* Ingest and manage documents in vector store
* Query and retrieve document content
* Manage document embeddings
* **Context Management**
* Manage context for different document types
* Set and retrieve PRD context
* Support for future context types (technical specs, user stories, etc.)
* **Knowledge Graph**
* Generate knowledge graphs from codebase queries
* Visualize relationships between code entities
* Analyze code structure and dependencies
* **API Endpoints**
* `/api/documents/*` - Document generation and formatting
* `/api/generate/*` - Document formatting utilities
* `/api/vector-store/*` - Vector store management
* `/api/agents/*` - AI agent operations
* `/api/context/*` - Context management for documents
* `/api/graph/*` - Knowledge graph generation and analysis
Note: JWT authentication support coming soon. All endpoints currently provide detailed OpenAPI documentation. * **Observability**
* OpenTelemetry instrumentation for distributed tracing
* Prometheus metrics endpoint at `/metrics`
* Comprehensive request/response tracking
* Custom business metrics
# CoreStory System Architecture
This document provides a high-level overview of how the CoreStory platform ingests, analyzes, and serves structured software intelligence through its API. The system is designed to process codebases and related technical artifacts in order to generate product specifications, technical documents, and knowledge graph representations. ---
## Core Components
### 1. **Ingestion Layer**
- Accepts Git URLs, file uploads, or local archives
- Extracts source files, documentation, and metadata
- Initiates chunking and embedding via the vector store pipeline
### 2. **Vector Store and Context Engine**
- Stores chunked and embedded documents
- Supports semantic search and document retrieval
- Feeds LLMs with scoped context for generation and reasoning
### 3.'
version: 1.33.0
servers:
- url: /
description: Current server
security:
- BearerAuth: []
tags:
- name: project-selections
paths:
/api/organizations/project-selections:
get:
tags:
- project-selections
summary: List the org's saved project selections
operationId: list_project_selections
responses:
'200':
description: Successful Response
content:
application/json:
schema:
items:
$ref: '#/components/schemas/ProjectSelectionResponse'
type: array
title: Response List Project Selections
default:
description: Error
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorSchema'
'404':
description: Not found
post:
tags:
- project-selections
summary: Save a project selection
operationId: create_project_selection
requestBody:
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectSelectionRequest'
required: true
responses:
'201':
description: Successful Response
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectSelectionResponse'
default:
description: Error
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorSchema'
'404':
description: Not found
/api/organizations/project-selections/{selection_id}:
put:
tags:
- project-selections
summary: Rename a selection or change what is in it
operationId: update_project_selection
parameters:
- name: selection_id
in: path
required: true
schema:
type: integer
title: Selection Id
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectSelectionRequest'
responses:
'200':
description: Successful Response
content:
application/json:
schema:
$ref: '#/components/schemas/ProjectSelectionResponse'
default:
description: Error
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorSchema'
'404':
description: Not found
delete:
tags:
- project-selections
summary: Delete a saved selection
operationId: delete_project_selection
parameters:
- name: selection_id
in: path
required: true
schema:
type: integer
title: Selection Id
responses:
'204':
description: Successful Response
default:
description: Error
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorSchema'
'404':
description: Not found
components:
schemas:
ErrorBody:
properties:
message:
type: string
title: Message
type:
type: string
title: Type
details:
additionalProperties: true
type: object
title: Details
description: Optional extra context for the error.
code:
anyOf:
- type: string
- type: 'null'
title: Code
description: Stable machine-readable code for clients that branch on the specific failure.
required_organization:
anyOf:
- $ref: '#/components/schemas/RequiredOrganization'
- type: 'null'
description: Set when the caller can retry after switching organization context.
type: object
required:
- message
- type
title: ErrorBody
ProjectSelectionRequest:
properties:
name:
type: string
maxLength: 120
minLength: 1
title: Name
description: What this set of projects is called.
project_ids:
items:
type: integer
type: array
minItems: 1
title: Project Ids
description: The projects in it.
type: object
required:
- name
- project_ids
title: ProjectSelectionRequest
ProjectSelectionResponse:
properties:
id:
type: integer
title: Id
name:
type: string
title: Name
project_ids:
items:
type: integer
type: array
title: Project Ids
created_at:
type: string
format: date-time
title: Created At
updated_at:
anyOf:
- type: string
format: date-time
- type: 'null'
title: Updated At
type: object
required:
- id
- name
- project_ids
- created_at
title: ProjectSelectionResponse
RequiredOrganization:
properties:
id:
type: string
title: Id
description: Clerk organization id the client should switch to.
name:
type: string
title: Name
description: Display name of that organization.
type: object
required:
- id
- name
title: RequiredOrganization
description: The organization a caller must be acting under before a denied request can succeed.
ErrorSchema:
properties:
error:
$ref: '#/components/schemas/ErrorBody'
type: object
required:
- error
title: ErrorSchema
securitySchemes:
BearerAuth:
type: http
scheme: bearer
bearerFormat: JWT
description: Enter the Bearer token from Clerk authentication
x-tagGroups:
- name: Ingest Your Codebase
tags:
- vector_store
- projects
- pre_ingestion
- reingestion
- name: Generate Code Intelligence
tags:
- documents
- document_generation
- document_formatters
- prd
- prd_version
- tech_spec
- quality_metrics
- sample_projects
- name: Query Your Codebase
tags:
- conversations
- workflows
- discovery
- context
- artifacts
- name: Manage and Inspect Intelligence
tags:
- api_debugging
- events
- version
- files
- cache
- token_tracking
- name: Authenticate and Manage Access
tags:
- clerk_authentication
- git_webhooks
- github_integration
- organizations
- api_key_management
- mcp_token_management
- user
- name: (Advanced) Prompt Tuning
tags:
- prompts
- name: MCP Protocol
tags:
- mcp_protocol
- name: Administration
tags:
- admin
x-provenance:
method: harvested
publisher: CoreStory
source: https://c2s.corestory.ai/openapi.json
note: split by refine-openapis from the provider's own published document, verified by fetch (openapi/_original/*.fetch.json);
stamped by stamp-openapi-provenance.py (roadmap#793)