bluesky feed query and retrieval, bluesky post search and filtering, mcp (model context protocol) resource exposure for bluesky data, context materialization and caching for bluesky data, at protocol authentication and session management, post metadata extraction and normalization

Bluesky

RepositoryFree

** - integrates with Bluesky API to query and search feeds and posts.

Open Source

/ 100

6 capabilities

Capabilities6 decomposed

bluesky feed query and retrieval

Medium confidence

Queries Bluesky's public API to retrieve feed data by connecting to the AT Protocol endpoints, parsing JSON responses, and materializing feed posts with metadata (author, timestamp, engagement metrics). Implements direct HTTP client integration with Bluesky's REST API rather than using a third-party SDK wrapper, enabling low-latency feed access without abstraction overhead.

Solves for

I need to fetch a user's home feed or timeline programmaticallyI want to retrieve posts from a specific Bluesky feed algorithmI need to get feed data with full post metadata for downstream processing

Best for

developers building Bluesky integrations or bots

teams building context servers or MCP-compatible tools

builders creating Bluesky analytics or monitoring systems

Requires

Bluesky account or API credentials

Network connectivity to Bluesky API endpoints (api.bsky.app)

HTTP client library (likely built-in to language runtime)

Limitations

Rate-limited by Bluesky API (typically 100-300 requests/min depending on endpoint)

No built-in pagination state management — caller must track cursors manually

Requires valid Bluesky credentials or public API access; private feeds require authentication

What makes it unique

Direct AT Protocol API integration without SDK abstraction layer, enabling tight control over request/response handling and minimal latency for context server use cases where feed data is materialized into MCP resources

vs alternatives

Lower overhead than Bluesky SDK wrappers because it speaks directly to AT Protocol endpoints, making it ideal for stateless context servers that need fast feed materialization

bluesky post search and filtering

Medium confidence

Implements search capability against Bluesky posts using the AT Protocol search endpoints, supporting keyword matching, author filtering, and temporal range queries. Returns ranked post results with relevance scoring and allows filtering by engagement metrics (likes, reposts) or post type (text, links, media). Uses query parameter composition to construct AT Protocol-compatible search requests.

Solves for

I need to search for posts matching specific keywords or topics on BlueskyI want to find posts from a specific author within a date rangeI need to filter posts by engagement level or content type for curation

Best for

developers building Bluesky search tools or discovery features

teams creating content curation or monitoring systems

builders implementing semantic search over Bluesky content

Requires

Bluesky API access (public endpoints, no auth required for basic search)

Query string with at least one search term

Understanding of AT Protocol post URIs and author DIDs for filtering

Limitations

Search is limited to public posts; private/unlisted content is not searchable

Search results may have 5-30 second latency due to indexing lag

No full-text semantic search (keyword-only); relevance ranking is basic

What makes it unique

Wraps Bluesky's native search API with composable filter chains (author, date, engagement) that can be combined without multiple round-trips, reducing latency for complex queries in context server scenarios

vs alternatives

More efficient than client-side filtering because it pushes predicates to the Bluesky API layer, avoiding transfer of irrelevant posts and reducing bandwidth

mcp (model context protocol) resource exposure for bluesky data

Medium confidence

Exposes Bluesky feeds and posts as MCP resources that can be consumed by LLM agents and context servers. Implements MCP resource handlers that wrap feed/post queries and present results as structured, queryable resources with standardized schemas. Enables LLM agents to access Bluesky data through a unified MCP interface without direct API knowledge.

Solves for

I want my LLM agent to access Bluesky feeds as MCP resourcesI need to expose Bluesky posts as context for an AI assistantI want to build an agent that can query and reason over Bluesky data

Best for

developers building LLM agents with Bluesky context

teams integrating Bluesky into Claude or other MCP-compatible AI systems

builders creating multi-source context servers that include social media

Requires

MCP server runtime (Node.js, Python, or language-specific MCP SDK)

MCP client that supports resource protocol (Claude, Cline, or custom agent)

Bluesky API credentials or public access

Limitations

MCP resource schema must be predefined; dynamic schema generation is not supported

Resource materialization adds ~100-300ms per query due to MCP serialization

No built-in caching of MCP resources; each agent query triggers a fresh API call

What makes it unique

Bridges Bluesky API and MCP protocol by implementing resource handlers that translate AT Protocol queries into MCP-compatible responses, enabling seamless LLM agent access to Bluesky without custom tool implementations

vs alternatives

More composable than custom tool definitions because it uses MCP's standardized resource model, allowing agents to discover and query Bluesky data through a consistent interface

context materialization and caching for bluesky data

Medium confidence

Materializes Bluesky feed and post data into an in-memory or persistent cache, enabling fast repeated access without hitting rate limits. Implements TTL-based cache invalidation and optional persistent storage (file, database) for context that needs to survive server restarts. Supports cache warming by pre-fetching feeds on startup or on a schedule.

Solves for

I want to cache Bluesky feed data to avoid rate limit exhaustionI need persistent storage of Bluesky posts for offline analysisI want to pre-warm context with popular feeds on server startup

Best for

teams running context servers with high query volume

developers building Bluesky bots that need to minimize API calls

builders creating offline-capable Bluesky tools

Requires

In-memory storage (built-in to runtime) or external cache store (Redis, SQLite, PostgreSQL)

TTL configuration (seconds or minutes)

Optional: persistent storage backend for durability

Limitations

In-memory cache is lost on server restart unless persisted

Cache invalidation is time-based (TTL); no event-driven invalidation on Bluesky updates

Stale data risk: cached posts may be outdated if feed is updated frequently

What makes it unique

Implements multi-tier caching (in-memory + optional persistent) with configurable TTL and cache warming, reducing API load for context servers that serve repeated queries over the same feeds

vs alternatives

More efficient than naive repeated API calls because it batches cache updates and supports pre-warming, reducing latency for common queries by 10-100x

at protocol authentication and session management

Medium confidence

Handles Bluesky/AT Protocol authentication by managing session tokens, refreshing credentials, and maintaining authenticated HTTP clients. Supports both user credentials (username/password) and app-specific tokens. Implements automatic token refresh to prevent session expiration during long-running operations.

Solves for

I need to authenticate with Bluesky API using my credentialsI want to maintain an authenticated session for multiple API callsI need to refresh my auth token before it expires

Best for

developers building authenticated Bluesky integrations

teams running long-lived context servers that need persistent auth

builders creating Bluesky bots or automation tools

Requires

Bluesky username and password, or pre-generated app token

Secure credential storage (environment variables, secrets manager)

HTTP client with cookie/header management

Limitations

Credentials must be stored securely; no built-in encryption or secrets management

Token refresh adds ~200-500ms latency on first call after expiration

No support for OAuth2 or delegated auth flows; requires direct credential storage

What makes it unique

Wraps AT Protocol's session token lifecycle with automatic refresh logic, eliminating the need for callers to manually handle token expiration or re-authentication

vs alternatives

Simpler than manual token management because it transparently refreshes credentials before expiration, reducing 401 errors and retry logic in calling code

post metadata extraction and normalization

Medium confidence

Extracts and normalizes metadata from Bluesky posts (author, timestamp, engagement metrics, media attachments, reply chains) into a consistent schema. Handles AT Protocol's nested data structures and converts them to flat, queryable formats. Supports extraction of embedded links, hashtags, and mentions for downstream processing.

Solves for

I need to extract structured metadata from Bluesky posts for analysisI want to normalize post data across different API responsesI need to identify links, hashtags, and mentions in posts

Best for

developers building Bluesky analytics or data pipelines

teams creating content analysis or moderation tools

builders implementing semantic indexing of Bluesky posts

Requires

Raw post JSON from Bluesky API

Knowledge of AT Protocol post schema (or use provided schema definitions)

Limitations

Extraction is schema-dependent; changes to AT Protocol may break parsers

Nested reply chains require recursive traversal; can be expensive for deep threads

Media attachment extraction is limited to metadata; does not download or process images/videos

What makes it unique

Implements AT Protocol-aware parsing that handles Bluesky's nested facet and embed structures, converting them to flat, queryable schemas without losing information

vs alternatives

More robust than generic JSON flattening because it understands AT Protocol semantics (facets, embeds, reply refs) and preserves structured relationships

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

Related Artifactssharing capabilities

Artifacts that share capabilities with Bluesky, ranked by overlap. Discovered automatically through the match graph.

MCP Server46

Bluesky MCP Server

Post, search, and interact on Bluesky social network via MCP.

user and post search with full-text indexingtimeline feed retrieval with cursor-based paginationat protocol-native post creation with rich text and embed supportmcp tool schema registration and invocation

4 shared capabilities

MCP Server18

MCP Sky

** - Bluesky feed for MCP related news and discussion by **[@brianell.in](https://bsky.app/profile/brianell.in)**

bluesky feed aggregation and curation for mcp ecosystem newsmcp community discussion indexing and discoveryreal-time mcp ecosystem monitoring and trend detection

3 shared capabilities

MCP Server19

PulseMCP

** ([API](https://www.pulsemcp.com/api)) - Community hub & weekly newsletter for discovering MCP servers, clients, articles, and news by **[Tadas Antanavicius](https://github.com/tadasant)**, **[Mike Coughlin](https://github.com/macoughl)**, and **[Ravina Patel](https://github.com/ravinahp)**

mcp server discovery and cataloging

1 shared capability

MCP Server24

Israel Statistics MCP

** MCP server that provides programmatic access to the Israeli Central Bureau of Statistics (CBS) price indices and economic data.

mcp resource discovery for available cbs indices and metadata

1 shared capability

MCP Server26

SAP ABAP MCP Server SDK

** - Build SAP ABAP based MCP servers. ABAP 7.52 based with 7.02 downport; runs on R/3 & S/4HANA on-premises, currently not cloud-ready.

mcp resource exposure from abap data sources

1 shared capability

MCP Server25

@ignitionai/mcp-template

ModelContextProtocol server with tools, prompts and resources

resource exposure and querying

1 shared capability

Best For

✓developers building Bluesky integrations or bots
✓teams building context servers or MCP-compatible tools
✓builders creating Bluesky analytics or monitoring systems
✓developers building Bluesky search tools or discovery features
✓teams creating content curation or monitoring systems
✓builders implementing semantic search over Bluesky content
✓developers building LLM agents with Bluesky context
✓teams integrating Bluesky into Claude or other MCP-compatible AI systems

Known Limitations

⚠Rate-limited by Bluesky API (typically 100-300 requests/min depending on endpoint)
⚠No built-in pagination state management — caller must track cursors manually
⚠Requires valid Bluesky credentials or public API access; private feeds require authentication
⚠Feed data is point-in-time snapshot; no streaming or real-time push support
⚠Search is limited to public posts; private/unlisted content is not searchable
⚠Search results may have 5-30 second latency due to indexing lag

Requirements

Bluesky account or API credentialsNetwork connectivity to Bluesky API endpoints (api.bsky.app)HTTP client library (likely built-in to language runtime)Understanding of AT Protocol feed identifiers and cursor-based paginationBluesky API access (public endpoints, no auth required for basic search)Query string with at least one search termUnderstanding of AT Protocol post URIs and author DIDs for filteringMCP server runtime (Node.js, Python, or language-specific MCP SDK)

Input / Output

Accepts: feed identifier (string, e.g., 'home', 'discover', or custom feed URI), optional pagination cursor (string), optional limit parameter (integer, 1-100), search query string (text, e.g., 'climate change'), optional author DID filter (string), optional date range (ISO 8601 timestamps), optional engagement threshold (integer, e.g., min_likes: 10), MCP resource request with query parameters (feed ID, search terms, filters), optional pagination tokens, feed identifier or post URI to cache, TTL value (integer, seconds), optional cache key prefix (string), username (string), password (string) or app token (string), raw post JSON object from Bluesky API, optional schema version (string, for backward compatibility)

Produces: JSON array of post objects, structured post metadata (author DID, URI, timestamp, like/repost counts), pagination cursor for next batch, ranked JSON array of matching posts, post metadata with relevance score, author information and engagement metrics, MCP resource response with structured post/feed data, JSON-LD or JSON schema-compliant resource representation, metadata for resource navigation and pagination, cached post/feed data (JSON), cache hit/miss indicator, cache metadata (age, TTL remaining), authenticated HTTP client (ready for API calls), session token (string, for manual reuse), token expiration timestamp, normalized post object with flat structure, extracted metadata (author DID, timestamp, metrics), list of embedded entities (links, hashtags, mentions), reply chain information (parent post, thread root)

UnfragileRank

Adoption15%(35% weight)

Quality14%(20% weight)

Ecosystem30%(25% weight)

Match Graph10%(15% weight)

Freshness75%(5% weight)

UnfragileRank is computed from adoption signals, documentation quality, ecosystem connectivity, match graph feedback, and freshness. No artifact can pay for a higher rank.

Type: Repository

6 capabilities

Visit Bluesky→

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** - integrates with Bluesky API to query and search feeds and posts.

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Capabilities6 decomposed

bluesky feed query and retrieval

Medium confidence

Solves for

I need to fetch a user's home feed or timeline programmaticallyI want to retrieve posts from a specific Bluesky feed algorithmI need to get feed data with full post metadata for downstream processing

Best for

developers building Bluesky integrations or bots

teams building context servers or MCP-compatible tools

builders creating Bluesky analytics or monitoring systems

Requires

Bluesky account or API credentials

Network connectivity to Bluesky API endpoints (api.bsky.app)

HTTP client library (likely built-in to language runtime)

Limitations

Rate-limited by Bluesky API (typically 100-300 requests/min depending on endpoint)

No built-in pagination state management — caller must track cursors manually

Requires valid Bluesky credentials or public API access; private feeds require authentication

What makes it unique

vs alternatives

Lower overhead than Bluesky SDK wrappers because it speaks directly to AT Protocol endpoints, making it ideal for stateless context servers that need fast feed materialization

bluesky post search and filtering

Medium confidence

Solves for

Best for

developers building Bluesky search tools or discovery features

teams creating content curation or monitoring systems

builders implementing semantic search over Bluesky content

Requires

Bluesky API access (public endpoints, no auth required for basic search)

Query string with at least one search term

Understanding of AT Protocol post URIs and author DIDs for filtering

Limitations

Search is limited to public posts; private/unlisted content is not searchable

Search results may have 5-30 second latency due to indexing lag

No full-text semantic search (keyword-only); relevance ranking is basic

What makes it unique

vs alternatives

More efficient than client-side filtering because it pushes predicates to the Bluesky API layer, avoiding transfer of irrelevant posts and reducing bandwidth

mcp (model context protocol) resource exposure for bluesky data

Medium confidence

Solves for

I want my LLM agent to access Bluesky feeds as MCP resourcesI need to expose Bluesky posts as context for an AI assistantI want to build an agent that can query and reason over Bluesky data

Best for

developers building LLM agents with Bluesky context

teams integrating Bluesky into Claude or other MCP-compatible AI systems

builders creating multi-source context servers that include social media

Requires

MCP server runtime (Node.js, Python, or language-specific MCP SDK)

MCP client that supports resource protocol (Claude, Cline, or custom agent)

Bluesky API credentials or public access

Limitations

MCP resource schema must be predefined; dynamic schema generation is not supported

Resource materialization adds ~100-300ms per query due to MCP serialization

No built-in caching of MCP resources; each agent query triggers a fresh API call

What makes it unique

vs alternatives

More composable than custom tool definitions because it uses MCP's standardized resource model, allowing agents to discover and query Bluesky data through a consistent interface

context materialization and caching for bluesky data

Medium confidence

Solves for

I want to cache Bluesky feed data to avoid rate limit exhaustionI need persistent storage of Bluesky posts for offline analysisI want to pre-warm context with popular feeds on server startup

Best for

teams running context servers with high query volume

developers building Bluesky bots that need to minimize API calls

builders creating offline-capable Bluesky tools

Requires

In-memory storage (built-in to runtime) or external cache store (Redis, SQLite, PostgreSQL)

TTL configuration (seconds or minutes)

Optional: persistent storage backend for durability

Limitations

In-memory cache is lost on server restart unless persisted

Cache invalidation is time-based (TTL); no event-driven invalidation on Bluesky updates

Stale data risk: cached posts may be outdated if feed is updated frequently

What makes it unique

Implements multi-tier caching (in-memory + optional persistent) with configurable TTL and cache warming, reducing API load for context servers that serve repeated queries over the same feeds

vs alternatives

More efficient than naive repeated API calls because it batches cache updates and supports pre-warming, reducing latency for common queries by 10-100x

at protocol authentication and session management

Medium confidence

Solves for

I need to authenticate with Bluesky API using my credentialsI want to maintain an authenticated session for multiple API callsI need to refresh my auth token before it expires

Best for

developers building authenticated Bluesky integrations

teams running long-lived context servers that need persistent auth

builders creating Bluesky bots or automation tools

Requires

Bluesky username and password, or pre-generated app token

Secure credential storage (environment variables, secrets manager)

HTTP client with cookie/header management

Limitations

Credentials must be stored securely; no built-in encryption or secrets management

Token refresh adds ~200-500ms latency on first call after expiration

No support for OAuth2 or delegated auth flows; requires direct credential storage

What makes it unique

Wraps AT Protocol's session token lifecycle with automatic refresh logic, eliminating the need for callers to manually handle token expiration or re-authentication

vs alternatives

Simpler than manual token management because it transparently refreshes credentials before expiration, reducing 401 errors and retry logic in calling code

post metadata extraction and normalization

Medium confidence

Solves for

I need to extract structured metadata from Bluesky posts for analysisI want to normalize post data across different API responsesI need to identify links, hashtags, and mentions in posts

Best for

developers building Bluesky analytics or data pipelines

teams creating content analysis or moderation tools

builders implementing semantic indexing of Bluesky posts

Requires

Raw post JSON from Bluesky API

Knowledge of AT Protocol post schema (or use provided schema definitions)

Limitations

Extraction is schema-dependent; changes to AT Protocol may break parsers

Nested reply chains require recursive traversal; can be expensive for deep threads

Media attachment extraction is limited to metadata; does not download or process images/videos

What makes it unique

Implements AT Protocol-aware parsing that handles Bluesky's nested facet and embed structures, converting them to flat, queryable schemas without losing information

vs alternatives

More robust than generic JSON flattening because it understands AT Protocol semantics (facets, embeds, reply refs) and preserves structured relationships

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

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GitHub Copilot52Extension

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Bluesky

Capabilities6 decomposed

bluesky feed query and retrieval

bluesky post search and filtering

mcp (model context protocol) resource exposure for bluesky data

context materialization and caching for bluesky data

at protocol authentication and session management

post metadata extraction and normalization

Related Artifactssharing capabilities

Bluesky MCP Server

MCP Sky

PulseMCP

Israel Statistics MCP

SAP ABAP MCP Server SDK

@ignitionai/mcp-template

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

About

Categories

Alternatives to Bluesky

Are you the builder of Bluesky?

Get the weekly brief

Data Sources

Bluesky

Capabilities6 decomposed

bluesky feed query and retrieval

bluesky post search and filtering

mcp (model context protocol) resource exposure for bluesky data

context materialization and caching for bluesky data

at protocol authentication and session management

post metadata extraction and normalization

Related Artifactssharing capabilities

Bluesky MCP Server

MCP Sky

PulseMCP

Israel Statistics MCP

SAP ABAP MCP Server SDK

@ignitionai/mcp-template

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

About

Categories

Alternatives to Bluesky

Are you the builder of Bluesky?

Get the weekly brief

Data Sources