Knowledge Repository Interface (MCP Server)

Cline and Claude Desktop Integration for the Semantic Knowledge Vault - persist, query, and structure insights with contextual understanding

This specialized MCP server facilitates interaction with a centralized Knowledge Vault instance, enabling users to commit and search stored knowledge using high-dimensional semantic vector matching directly within the Cline and Claude Desktop interfaces.

Associated Systems

This MCP server is architected to interface with The Semantic Vault, which functions as the core infrastructure for storing and retrieving vectorized knowledge artifacts.

The Vault provides the necessary backend API layer for this MCP server, empowering users to: - Deposit information chunks enriched with vector embeddings for meaning-based searching - Categorize retained data using user-defined partitions (buckets) - Execute complex queries based on conceptual similarity, transcending mere keyword matching - Fetch archived data complete with contextual metadata - Identify conceptually analogous entries - Monitor the assimilation status of deposited knowledge items

For comprehensive details on deploying or utilizing the backend Vault system, refer to the Semantic Vault documentation.

Core Capabilities

• Knowledge Ingestion: Record meticulously formatted entries into your Vault, complete with provenance data and associated attributes.
• Information Retrieval: Query the knowledge base using advanced semantic matching algorithms, supporting paginated results and chronological ordering.
• Partition Access: Retrieve the entirety of stored knowledge or isolate entries belonging to specific organizational containers.
• Container Administration: Establish new organizational partitions or decommission existing ones.
• Artifact Manipulation: Modify or eradicate pre-existing knowledge entries.
• Contextual Discovery: Uncover entries exhibiting high conceptual overlap with a specified artifact.
• Assimilation Verification: Gauge the processing state of any given knowledge item.
• Insight Structuring: Apply a rigorous template (system prompt) to standardize data presentation prior to commitment.
• Operational Metrics: Review current service tiers, consumption statistics, and resource ceilings.

Deployment Procedures

The server environment has been pre-configured for Cline usage. Prerequisite: A functional Semantic Vault instance (either locally hosted or accessing the managed service at memorybox.amotivv.ai).

Integration via Desktop Extension (Recommended Path)

The most streamlined method for incorporating the Knowledge Vault with Claude Desktop involves the dedicated Extension:

1. Obtain the latest package file, typically named memory-box.mcpb, from the official releases repository.
2. Launch Claude Desktop.
3. Navigate to Configuration -> Extensions.
4. Select the option to "Install from file".
5. Point to the downloaded memory-box.mcpb file.
6. In the extension configuration pane, input your Knowledge Vault API credential.

The extension will automatically finalize all requisite environment variable setups and tool mappings.

Installation through Smithery

To automate the deployment of the Knowledge Vault MCP Server for Claude Desktop using Smithery:

npx -y @smithery/cli install @amotivv/memory-box-mcp --client claude

To complete the initialization sequence:

1. Modify the Cline MCP configuration file located at: ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json

2. Inject your Vault authentication key into the MEMORY_BOX_TOKEN environment variable definition: json "memory-box-mcp": { "command": "node", "args": [ "<path-to-repository>/build/index.js" ], "env": { "MEMORY_BOX_API_URL": "https://memorybox.amotivv.ai", "MEMORY_BOX_TOKEN": "your-secret-key-here", "DEFAULT_BUCKET": "CoreKnowledge" }, "disabled": false, "autoApprove": [] }

3. The default storage partition can be overridden by altering the DEFAULT_BUCKET value.

Operational Usage

Post-configuration, the following capabilities become accessible within the Cline environment:

Knowledge Ingestion

Deposit data into the Vault adhering to precise structural mandates:

Invoke the save_memory function to archive the following insight regarding vector storage architectures: "Vector databases such as pgvector are engineered to manage and interrogate high-dimensional vector representations critical for advanced semantic search deployments."

Parameters: - text (Mandatory): The conceptual payload to be stored. - bucket_id (Optional): The designated container for this artifact (Default: "CoreKnowledge"). - format (Optional): Boolean flag dictating application of the standard system template (Default: true). - type (Optional): Classification of the knowledge unit (e.g., TECHNICAL, RULING, IMPLEMENTATION, PRINCIPLE, REFERENCE, APPLICATION, FACT) for template adherence (Default: "TECHNICAL"). - source_type (Optional): Origin identifier for the knowledge input (Default: "llm_plugin"). - reference_data (Optional): Supplementary metadata detailing the source and contextual frame.

Knowledge Query

Execute a search based on conceptual meaning:

Issue a request to the search_memories function to locate data pertaining to "vector indexing methods"

Parameters: - query (Mandatory): The textual representation of the conceptual search term. - debug (Optional): Flag to include diagnostic artifacts in the output (Default: false).

Retrieve All Artifacts

Fetch the complete inventory:

Execute the get_all_memories function to display every archived item.

Access Partition Contents

Fetch data exclusively from a specified organizational unit:

Command the get_bucket_memories function to present all entries within the "ResearchLog" partition.

Parameters: - bucket_id (Mandatory): The identifier for the partition whose contents are sought.

Insight Structuring Utility

Process and format text according to the established schema without committing it to storage:

Use the format_memory function to render this text according to the schema: "Vector databases like pgvector store and query high-dimensional vectors for semantic search applications."

Parameters: - text (Mandatory): The data block requiring transformation. - type (Optional): The knowledge classification for formatting context (Default: "TECHNICAL").

Discover Related Entries

Identify artifacts highly similar in concept to a known entry:

Invoke the get_related_memories function using the artifact identifier 123.

Parameters: - memory_id (Mandatory): The unique identifier of the anchor artifact. - min_similarity (Optional): The required correlation coefficient floor (range 0.0 to 1.0) (Default: 0.7).

Verify Assimilation State

Determine the current processing status of an entry:

Execute the check_memory_status function utilizing artifact identifier 123.

Parameters: - memory_id (Mandatory): The unique identifier for the entry under status review.

Obtain Utilization Report

Request a summary of usage statistics and account tiering:

Use the get_usage_stats function to present my current operational level and consumption figures.

This function yields: - Details regarding the active service tier (e.g., complimentary, standard, premium, inherited). - User status indicators and constraint enforcement parameters. - Cumulative consumption metrics for the present billing cycle (storage operations, query counts, remote calls). - Data throughput volume, presented in an easily digestible format. - Allocated resource thresholds, if applicable to the current plan. - A detailed breakdown categorized by operation type.

This operation requires no input parameters.

List All Partitions

Obtain a registry of all active storage containers:

Execute the get_buckets function to display the full list of available partitions.

This function returns a structured list detailing partition names, unique IDs, the count of associated artifacts, and their respective initialization timestamps.

Instantiate Partition

Create a new organizational container for knowledge segregation:

Invoke the create_bucket function to establish a new partition named "InnovationPipeline".

Parameters: - bucket_name (Mandatory): The descriptive label for the partition to be initialized.

Archive Partition

Remove an existing knowledge partition:

Issue the delete_bucket function targeting the partition labeled "LegacyFiles".

Parameters: - bucket_name (Mandatory): The label of the partition slated for removal. - force (Optional): A flag compelling deletion even if artifacts remain within (Default: false).

Revision of Knowledge Artifact

Update the content, relocation, or descriptive metadata of a stored entry:

Call the update_memory function to revise artifact ID 123 with revised content: "The definitive specification for vector database interaction has been updated."

Parameters: - memory_id (Mandatory): The unique identifier of the artifact requiring modification. - text (Optional): The newly mandated content payload. - bucket_id (Optional): The destination partition for the artifact. - reference_data (Optional): Revised contextual linkage and metadata.

Eradicate Knowledge Entry

Permanently remove a specific artifact from the Vault:

Command the delete_memory function to purge artifact ID 123.

Parameters: - memory_id (Mandatory): The unique identifier of the artifact scheduled for deletion.

Configuration Customization

System Template Modification

The Knowledge Vault MCP server employs a defined system template to govern the structural output of stored knowledge items. This template can be wholly revised to align with specific organizational documentation standards.

Default System Template

The standard template enforces detailed formatting rules contingent on the knowledge type:

You are an expert knowledge curator. When saving artifacts to the Semantic Vault via Memory Box, adhere strictly to these advanced structuring protocols:

1. STRUCTURAL MANDATE: Organize entries based on their inherent classification:
   - TECHNICAL: "TECH SPEC - [Core Subject]: [Detailed, precise explanation including critical parameters]"
   - RULING: "GOV. DECISION - [Subject of Judgment]: [Final verdict] predicated on [justification]. Alternatives explored: [options assessed]."
   - IMPLEMENTATION: "PROCEDURE - [Challenge Summary]: [Step-by-step execution details that resolved the constraint]"
   - PRINCIPLE: "FUNDAMENTAL - [Concept Name]: [Unambiguous definition of the principle supported by relevant illustrations]"
   - REFERENCE: "RESOURCE LOCATOR - [Subject Area]: [URI, utility name, or document handle] referencing [primary utility]."
   - APPLICATION: "UTILITY OVERVIEW - [Software Name]: [User-facing description] followed by [underlying technical schema]."

2. PRESENTATION STANDARDS:
   - ENSURE FOCUSED CONTENT: Each archived entry must encapsulate one singular, coherent idea or piece of information.
   - UTILIZE RICH VOCABULARY: Incorporate both specialized lexicon AND accessible, plain-language equivalents.
   - EMBED RETRIEVABLE TERMS: Initiate the entry with terminology likely to be used in subsequent searches.
   - PROPORTION DETAIL: Provide a balance between high-level abstraction and granular technical specifics.
   - LENGTH CONSTRAINT: Maintain entry length between 50 and 150 words.
   - TIMESTAMPING: Always affix the current date in ISO 8601 format (YYYY-MM-DD).

3. STORAGE ATTRIBUTE SPECIFICATION:
   - Utilize the "text" attribute for the fully formatted knowledge payload.
   - Designate the "source_type" attribute as "llm_plugin".
   - Supply granular "reference_data" detailing origin and session context.

4. CONTEXTUAL DATA SCHEMA:
   - source.platform: Specify the originating environment (e.g., "claude_desktop", "cline_interface").
   - source.type: Must be set to "llm_plugin".
   - source.version: Version metadata (optional).
   - context.conversation_id: Linkage ID for related session artifacts.
   - context.message_id: Specific message pointer (optional).

5. SPECIALIZED FORMATS:
   - For user characteristics, preferences, or facts: "YYYY-MM-DD: PERSONAL FACT: [User] exhibits [attribute/preference/detail]"
   - For external resource pointers: Document precise location and retrieval instructions.

6. NEIGHBORING ARTIFACTS STRATEGY: Following a successful search, proactively check for contextually proximate entries via the get_related_memories function, utilizing the ID obtained from the search response. Present these supplementary artifacts to enrich the user's understanding.

7. RETRIEVAL FORESIGHT: Before finalizing storage of any critical insight, perform a mental check: "What search queries would successfully surface this information later?" Ensure these terms are explicitly integrated.

Template Customization Procedure

To substitute the default template with a bespoke version:

1. Access the Cline MCP configuration file at: ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json

2. Integrate your revised template content into the SYSTEM_PROMPT environment variable setting: json "memory-box-mcp": { "command": "node", "args": [ "<path-to-repository>/build/index.js" ], "env": { "MEMORY_BOX_API_URL": "https://your-vault-endpoint", "MEMORY_BOX_TOKEN": "your-access-credential", "DEFAULT_BUCKET": "CoreKnowledge", "SYSTEM_PROMPT": "Your entirely custom knowledge structuring directive goes here..." }, "disabled": false, "autoApprove": [] }

A template source file is provided at <path-to-repository>/system-prompt-template.txt for convenient modification.

1. Relaunch Cline to activate the revised template structure.

Template Management Utility

The Knowledge Vault MCP server includes a CLI utility for template administration:

# View the currently active system template
cd <path-to-repository>
npm run prompt-helper -- view

# Revert to the factory-default system template
cd <path-to-repository>
npm run prompt-helper -- reset

# Verify the syntax integrity of a modified template
cd <path-to-repository>
npm run prompt-helper -- validate

Supplementary Configuration Variables

You possess the capacity to modify these environment parameters:

• MEMORY_BOX_API_URL: The network address pointing to your deployed Knowledge Vault instance.
• MEMORY_BOX_TOKEN: The requisite authentication key for accessing the Vault.
• DEFAULT_BUCKET: The designated storage partition used absent any explicit specification during data submission.

Issue Resolution

Should operational anomalies arise:

1. Confirm that the Vault access credential has been correctly provisioned.
2. Ensure the Knowledge Vault instance is operational and reachable via the network.
3. Scrutinize the Cline diagnostic logs for specific error reports.

Development Cycle

To implement modifications to the server logic:

1. Edit source files within the <path-to-repository>/src/ directory.
2. Recompile the server executable: cd <path-to-repository> npm run build
3. Restart Cline to ensure the modifications take effect.

Constructing the Desktop Package

To generate the final distributable Desktop Extension package:

1. Install required build dependencies: npm install

2. Initiate the extension compilation process: npm run build-extension

3. The finished package file, dist/memory-box.mcpb, will be situated in the distribution directory.

Release Management Workflow

1. Increment the version number within package.json.
2. Append relevant changes to CHANGELOG.md.
3. Commit all modifications to version control.
4. Publish a new release tag on GitHub.
5. Attach the generated memory-box.mcpb file as an asset to the release record.

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